Title: Deep learning of binary partition trees for image analysis
Keywords : Hierarchical representations, Binary partition trees, Deep learning, Ultrametrics, Computer Aided Diagnosis of Skin lesions.
Subject
There are many representations of digital images, each adapted to different contexts. In this thesis we are interested in hierarchical representations of images. These representations allow, from an over-segmentation of an image into super-pixels, to perform merging of regions at different scales. Such hierarchical representations allow to capture image features at different scales simultaneously, and are easily interpreted and manipulated by a human. Building good quality hierarchical representations is a very important step in image analysis. In image analysis, binary partition trees (BPT) are a popular hierarchical representation. Their construction relies on several key elements: an initial partition, a region model, a merging criterion, a merging order. This BPT construction often relies on region descriptors that are poorly suited to the data and on heuristic and greedy hierarchical clustering methods. We propose to take advantage of deep learning for the construction and manipulation of BPTs. The tree construction will then be able to exploit deep descriptors of superpixels, to learn the similarity between these descriptors and finally to have a learned merging criterion. As an ultrametric is a dual representation of a hierarchical representation, deep learning methods can be considered to learn not the ABP but directly the ultrametric from a graph representing the over-segmentation and by explicitly minimizing a cost function. The semantic segmentation of an image can then be seen as either a learned labeling of the vertices of the BPT or the learning of a cut in the BPT. A tree being a graph, convolution neural networks on graphs can be considered for this (convolution and pooling being very particular given the tree structure of the graph). Finally, applications in health (melanoma of the skin) and in satellite imagery will be made.
Qualifications
Candidates must have an MSc or engineering degree in a field related to computer science, electrical engineering, or applied mathematics, with strong programming skills (in particular with deep learning frameworks). Experience with image processing will be a plus. Candidates are expected to have abilities to write scientific reports and communicate research results at conferences in English.
Information and application:
Applications should include the following documents in electronic format: i) A short motivation letter stating why you are interested in this thesis, ii) A detailed CV describing your past research background related to the position iii) The transcripts for master degrees. iv) The contact information for three references (do not include the reference letters with your applications as we will only ask for the reference letters for short-listed candidates). Please send your application package to [email protected] and [email protected]. The position will start in October 2023 and will be located in Caen, France. Ideally located in the heart of Normandy, two hours from Paris and just 10 minutes away from the beaches, Caen, William the Conqueror’s hometown, is a lively and dynamic city.
Detailed pdf version
Available at https://lezoray.users.greyc.fr/tmp/sujetTheseLezoray2023_en.pdf
Please circulate this to any students that might be interested
We invite applications for the fully funded PhD studentship above. This PhD is suitable for a non-veterinary surgeon provided the applicant has strong programming skills. Specific training related to the machine learning/statistical areas will be provided as needed, together with the racehorse and veterinary aspects, such as endoscopy and upper airway disorders, though there is no requirement for direct animal work.
This project is well suited for PhD training in a novel area of interdisciplinary research, providing the opportunity to explore varied approaches for the application of advanced analysis and forming the basis of a substantial long-term research programme.
Funding: Based on our Langford campus, the four-year full-time PhD is generously funded by the Horserace Betting Levy Board. International students are welcome to apply but must be able to fund the difference between UK and International tuition fees.
Deadline: 14th April 2023
https://www.findaphd.com/phds/project/advanced-analytics-applied-to-endoscopic-analysis-of-upper-airway-function/?p152003
We are seeking two postdoctoral researchers to join the Vision, Language and Reading group at the Computer Vision Center (CVC), in Barcelona, Spain, focused on (1) COMPUTER VISION and (2) FEDERATED LEARNING AND DIFFERENTIAL PRIVACY.
The positions are available for a minimum of 2 years, and are linked to the “European Lighthouse on Secure and Safe AI” (ELSA), a European Project funded by Horizon Europe and backed by the ELLIS network of excellence. The project covers research topics that include robustness, privacy and human agency and will develop use cases in areas such as autonomous driving, robotics, health and document intelligence.
CANDIDATE ’S PROFILE
The candidate should possess a PhD in machine learning or computer vision and have a strong publication record. We are looking for candidates who have publications in top conferences like CVPR, ECCV, ICCV, ICDAR, NeurIPS, ICML, ICLR.
The candidate should have a strong background in machine learning and computer vision. Experience on document image analysis and/or visual question answering would be positive. The applicants are expected to be fluent in both oral and written communication in English. They should work well in a team while demonstrating initiative and independence. The candidate is expected to co-supervise PhD students.
The successful candidate is expected to contribute to the design and development of AI solutions for document understanding, employing privacy preserving techniques and infrastructures set up by the ELSA project.
THE COMPUTER VISION CENTER
The selected candidate will work in the Computer Vision Centre (CVC), Barcelona, a research institute comprising more than 130 researchers and support staff, dedicated to computer vision research and knowledge transfer. With a strong international projection and links to the industry, the Computer Vision Centre offers an exciting environment for scientific career development. The Computer Vision Centre has a plan for expansion of its permanent research staff base and has received the “HR Excellence in Research” award as a provider and supporter of a stimulating and favourable working environment.
The direct responsible for these posts will Dr Dimosthenis Karatzas, leading the Vision, Language and Reading research group at the CVC.
Barcelona is a vibrant city and an important Artificial Intelligence hub. The high quality of life is combined with an open and international looking character of the city. Barcelona is very well connected by air, sea and ground transportation. The region of Catalonia boosts its own AI strategy, in which the CVC is a key player.
RESEARCH CONTACT
If you are interested in the position, please contact Dr Dimosthenis Karatzas for more information and applications ([email protected])
APPLICATION PROCESS
Apply by filling in the online form at: Computer Vision: http://www.cvc.uab.es/blog/2023/01/11/postdoc-position-in-computer-vision/ FL and DP: http://www.cvc.uab.es/blog/2023/01/11/postdoc-position-in-computer-vision/
MORE INFO
ELSA project: https://elsa-ai.eu/ Computer Vision Center: http://www.cvc.uab.es/ Vision, Language and Reading group: https://www.vlr.ai/
We are currently seeking a research scientist or postdoctoral researcher. The successful candidate is expected to develop algorithms of weakly- and self-supervised learning, transfer learning, and/or AutoML for global high-resolution land cover mapping (semantic segmentation), 3D reconstruction, and 3D semantic change understanding. We welcome candidates with experiences and expertise in machine learning, computer vision, computer graphics, point cloud processing, and/or SAR signal processing. For more details, see here.
RIKEN Special Postdoctoral Researchers Program
RIKEN Special Postdoctoral Researchers (SPDR) program provides young scientists with the opportunity to conduct autonomous and independent research at RIKEN for three years. Qualified candidates of all nationalities can apply for the program. For more details, see here.
https://www.riken.jp/en/careers/programs/spdr/
Clifford Broni-Bediako RIKEN Center for Advanced Intelligence Project Goal-Oriented Technology Research Group Geoinformatics Unit at The University of Tokyo https://aip.riken.jp/ https://www.geoinformatics2018.com/ [email protected]
The crucial role of data protection in safeguarding personal information, preventing malicious use of data, and ensuring responsible handling of data by organizations is now widely acknowledged. We have an opening on this subject for a PhD position with the objective to develop new solutions to help data providers who wish to share their data to better understand it, and to choose the best-suited data protection policies. The PhD Student will be investigating techniques for profiling and linking datasets that would help data providers to gain insight into their data and to choose data protection strategies that go beyond privacy protection to take into account the protection of the data provider's economic assets. We aim to provide an end-to-end solution that helps data providers understand their data, identify the links that connect them as well as the links that connect them to external datasets, identify links that could be used maliciously to obtain privacy-intrusive information, and protect their datasets accordingly before sharing. The problems investigated and solutions developed will be guided and validated within case studies in the fields of health and economics.
The successful candidate will enroll as a PhD student in the Computer Science department of the Paris Dauphine University-PSL (under the co-direction of Khalid Belhajjame and Daniela Grigori) and will become a member of the Data Science team of the same university. Paris Dauphine University is located in the city of Paris, and is a member of PSL (Paris Sciences et Lettres). PSL is the first French university in Times Higher Education ranking.
We seek strongly motivated candidates prepared to dedicate to high quality research. The candidate should have (or be close to obtaining) a Master's degree or equivalent in computer science or applied mathematics.
Interested candidates are invited to send the following to [email protected] and [email protected]
academic CV
academic transcripts of BSc and MSc
one page motivation letter explaining why the candidate is suitable for the position
contact details of two referees
The Munich Center for Machine Learning is looking for up to ten PhD students for positions starting in July 2023.
Qualifications
Master Degree or equivalent in one of the following fields (must be completed no later than 2 months before start of PhD position, July 1st, 2023): informatics, artificial intelligence, machine learning, mathematics, statistics, data science, or physics
Excellent grades
A very good command of the English language
Strong scientific motivation
Interest in interdisciplinary research
Application deadline February 28th, 2023
Required Documents
Research project proposal (2 pages)
Cover letter of 1-2 pages in which you explain why you would like to join our center, and what qualifications you have to do so
Academic CV (including, among other things, your list of publications)
Writing sample in English on a topic in the focus of the three domain areas of the MCML: You may submit a published paper, a part of your Master-thesis, or any other piece of writing that indicates your skill. A writing sample should not exceed 15 pages.
Proof of English language proficiency (Cambridge Certificate, IELTS, TOEFL) of at least Level C1 (or higher), if your first language is not English
Names of three MCML PIs you would like to work with (check out here) Names and contact information for one to two referees who agree to fill out our online reference form on your behalf
Apply here - https://www.portal.graduatecenter.uni-muenchen.de/ocgc/mcml
Dr. Arielle Helmick Munich Center for Machine Learning TUM General Manager
School of Computation, Information and Technology Informatics 9 Boltzmannstrasse 3 85748 Garching Germany
Tel: +49-89-289-17786 Fax: +49-89-289-17757 Office: 02.09.042 Mail: [email protected]
Description of the offer - The Software Engineering Laboratory for Scientific Applications is looking for a research engineer (M/F) specialized in signal and image processing to:
Contribute to the upstream development of data analysis tools for the processing of data in physics. This research and development mission aims to develop and study innovative numerical methods, in particular based on machine learning, for solving data analysis problems, transversal to scientific data processing applications at IRFU .
Develop and validate software solutions for data analysis within astrophysics collaborations such as the LISA space mission (Laser Interferometry Space Antenna) or more generally fundamental research missions at IRFU.
Participate in the scientific animation of the IRFU, at the interface between data analysis and applications in physics.
These activities will be carried out within a team of research engineers in software engineering and data analysis/signal processing and in collaboration with project teams including physicists and engineers from IRFU departments.
Candidate profile
Researcher with a signal processing/image/data analysis profile, you have solid skills in signal processing, image processing and software programming (particularly in Python language, a good knowledge of modern C++ being an undeniable plus) .
You have in-depth knowledge of machine learning and related development tools (e.g. PyTorch).
You also have minimal experience of development methodologies and tools essential to a professional activity such as software life cycle management (git) or continuous integration (GitLab CI).
You have experience and an appetite for teamwork within collaborations at the interface between applied mathematics and applications in physics.
To apply, contact me or apply at https://www.emploi.cea.fr/offre-de-emploi/emploi-ingenieur-chercheur-en-traitement-du-signal-traitement-d-images-et-intelligence- artificial-h-f_25623.aspx
As part of this EFELIA MIAI project, the IUT departments of the UGA will develop training actions in Intelligence Artificial in GOAL3, especially in their Situations Learning and Assessment, related to advanced development and bigdata. As such, they are looking for an educational engineer that can help in the development of topics related to the lessons resources as well as assistance in the choice and implementation of appropriate teaching practices.
*Main missions*
Under the authority of the Administrative Director of IUT2 Grenoble, you will have the following missions:
Participate in the project management of innovation projects pedagogical and digital in Artificial Intelligence within the IUT of Grenoble.
Search for real datasets that may give rise to educational situations within the framework of the GOAL.
Study and ensure the project management of innovation projects pedagogical and digital in Artificial Intelligence with the EFELIA project partners (UGA, Grenoble INP, MIAI, CNA, CMQ)
Promote the evolution of teaching practices for the teaching of Artificial Intelligence. To be able to respond to requests for support from teachers and help the implementation of innovative devices.
The details of the position are available on the UGA website
https://emploi.univ-grenoble-alpes.fr/offres/doctorants/ingenieur-e-pedagogique-pour-projets-en-intelligence-artificielle-1204137.kjsp?RH=1135797159702996
*To apply*
Follow the link above and click on "Apply"
*For further information on the position*, contact
Ms. Agnès FRONT, head of the STID department at IUT2 [email protected]
Mr. François PORTET, IT department [email protected]
The Université de Lorraine (France) invites applications for a postdoctoral Researcher in Natural Language Processing and statistical learning for Health. The position is attached to a new scientific project involving three research units specialized in natural language processing (Research Center for Computer Processing and Analysis of the French Language - ATILF), applied mathematics (Mathematics Research Institute - IECL) and cancer (Research Center for Automatic Control - CRAN).
The main objective is to propose new methodologies and an innovative framework for the development of personalized medicine of low-grade brain tumors based on the latest advances in natural language processing and statistical learning. The research will investigate methods to automatically retrieve relevant information based on medical data about patients as well as scientific data publications. The precise research subject within this framework is open to discussion.
Terms and tenure This two-year position will be based at the ATILF, Research Center for Computer Processing and Analysis of the French Language (Nancy, France).
The duration can not exceed 24 months. The ATILF (https://www.atilf.fr/laboratoire/presentation-english/) is a research unit in (computational) linguistics, including expertise in natural language processing and terminology. Within the framework of multidisciplinary activities, the recruited researcher will be required to interact frequently with two other partner research centers of the project, the IECL and the CRAN, also located in Nancy, as well as to the neuro-oncology department of the regional hospital (CHRU) of Nancy. The target start date for the position is April-June 2023. Salary depends on experience.
How to apply Applicants are requested to submit the following materials: - A cover letter applying for the position
- Full CV and list of publications
- Academic transcripts (unofficial versions are fine)
Applications will be considered as they arise, but not later than end of March 2023.
Applications are only accepted through email. All documents must be sent to Mathieu Constant ([email protected]), Marianne Clausel ([email protected]) and Hélène Dumond ([email protected]).
Job location - Nancy, France
Requirements - PhD in natural language processing, computer science, machine learning or applied mathematics (PhD from the Université de Lorraine are excluded).
Skills
Expert knowledge of natural language processing
Good knowledge of statistical learning
Good programming skills
Experience in the interaction with biologists and clinicians may be a plus
Working in a multidisciplinary team
The ANR project ECLADATTA (involving IRIT, ORANGE, EURECOM) will start on March 15th, 2023.
A detailed offer for a 24-month post-doc within the MELODI team of IRIT (Toulouse) will be published in early February 2023. This offer will focus on the joint extraction of relations in texts and tables for the enrichment of knowledge graphs.
The project partners will provide an annotated corpus, as well as a set of tools based on rules and/or machine learning algorithms.
Each of the tools is dedicated to a specific task (extraction of relations from tables or from written text), and the objective of the post-doc is to proposes approaches that will enable these tools to be improved by mutual enrichment. In addition, the consistency of relations extracted from different sources (table, text, knowledge graph) should be cross-validated.
We are looking for a motivated, autonomous candidate, able to work in a team, fluent in English and French, competent in programming, and with research experience in natural language processing and/or semantic web and knowledge graphs.
*Contacts*: Nathalie Aussenac-Gilles ( [email protected] )
Mouna Kamel ( [email protected] )
Veronique Moriceau ( [email protected] )
An INRAE research engineer position is open in the UMR FARE in Reims on "Scientific Computing and Artificial Intelligence". The job description and the contacts to be reached are available on the INRAE jobs website:
https://jobs.inrae.fr/concours/concours-externes-ingenieurs-cadres-techniciens-hf/ir23-transform-2
The position is for a joint project with Fraunhofer IIS in Erlangen. The topic will be new digital signal processing approaches for next generation video coders.
The role would be to develop these algorithms, implement them in software (e.g. Python), and test them.
The position is for 3 years, but can be extended for finishing a Ph.D. on the topic. There will be an initial evaluation after a year.
Necessary qualifications are a Masters degree in Electrical Engineering or Computer Science, with a strong background in digital signal processing for audio and/or video. Excellent written and oral communication skills.
Applicants should submit a curriculum vitae including a short letter of interest, list of publications and a list of 2 referees (including contact information).
For further information and applications, please contact Prof. Gerald Schuller ([email protected]) Recruitment will continue until the position is filled.
Prof. Dr.-Ing. Gerald Schuller, email:[email protected] Institut fuer Medientechnik, TU Ilmenau phone: +49 3677 69 2756 Helmholtzplatz 2, 98693 Ilmenau, Germany GSM: +49 160 978 23032 Fraunhofer-Institut Digitale Medientechnologie
We are looking to fill one position for a researcher with a PhD degree at LASIGE (https://www.lasige.pt), a research unit at the Faculty of Sciences, University of Lisbon, from April 2023.
The successful candidate will work alongside a collaborative research team recognised as Excellent by the Portuguese government agency for science and technology FCT.
The researcher will be given excellent conditions to develop cutting-edge research on the following topics:
Accessibility and Ageing
Cyber‐physical Systems
Data and Systems Intelligence
Health and Biomedical Informatics
Reliable Software Systems
Resilient Distributed and Networked Systems
Requirements: Applicants should hold a doctoral degree in Computer Science or areas related to LASIGE research lines (see topics above)
Application period: February 13 to March 12, 2022
Public notice is available at: https://euraxess.ec.europa.eu/jobs/65310 and https://ciencias.ulisboa.pt/concursos?id=4191
Notwithstanding what is stated in the notice, it is expected that the contract can extend until the end of 2024. For further information on this and other inquiries, please e-mail [email protected].
Nuno Cruz Garcia Assistant Professor Department of Informatics Faculty of Sciences, Univ. of Lisbon Web: https://ncgarcia.github.io/
Full-time (100%) fixed-term contract of two years
for the Centre de traitement automatique du langage (Cental) within the Institut Langage & Communication (IL&C) in UCLouvain (Louvain-la-Neuve)
Start date : as soon as possible
This postdoctoral position offer is part of a research project led by the Cental (https://uclouvain.be/fr/instituts-recherche/ilc/cental) around legal data processing.
Regarding the concrete application, the project aims at automatizing the analysis of documents related to clinic trials (meeting minutes, legal documents, contracts, ...) to assess their compliance to RGPD. The proposed solution should thus be flexible enough to, on one hand, ensure that the model(s) can be adapted to the various document types and, on the other hand, limit the need of specialists' expertise for training data annotation. In consequence, the scientific core of this project is directly related fo the question of few-shot learning, which we intend to address through active learning and meta-learning.
The role of the hired postdoc will be to (1) develop the resources needed for learning, (2) implement an architecture that incorporates active learning and meta-learning, (3) evaluate the models and (4) implement the components into a web service. The postdoc will also be required to disseminate the results through scientific publications and/or reports.
Work environment:
CENTAL is part of the Institut Langage & Communication (https://uclouvain.be/fr/instituts-recherche/ilc), in UCLouvain.
This university is located in Louvain-la-Neuve, Belgium (https://uclouvain.be/fr/sites/louvain-la-neuve), a walkable city, that offers a pleasant and dynamic living environment. The research project will be supervised by Patrick Watrin.
Required skills:
A completed PhD in Computer Science, Machine Learning, NLP or a similar domain.
Excellent programming skills:
Python
TensorFlow/Keras or PyTorch
Linux (server administration)
Knowledge of the main supervised learning algorithms and deep learning algorithms is required
A good knowledge of the main NLP tools and algorithms is a plus
Strong research track record (publications, conferences, etc.)
Autonomy, teamwork, ability to understand and analyze needs, adaptability
Excellent command of the French language (at least C1) and good command of English (at least B2)
Conditions:
Fixed-term contract of one year, renewable once
Salary based on experience, ranging from 4250€ to 4850€ (monthly, gross)
The position requires residency in Belgium. Candidates from outside the EU are responsible for obtaining the adequate visa and/or permits, with support from the UCLouvain.
How to apply:
Deadline : March 31
The application file should be sent electronically to Patrick Watrin ([email protected]) and contain:
A detailed resume showing the adequate qualifications and skills, as well and the scientific/academic experiences and publications;
A cover letter in french, describing your interest for the role, how your profile complies with the project's needs, etc.;
A recommendation letter in french or in english.
The shortlisted candidates will be invited to participate in a remote video call (details will be communicated in a timely manner).
Inria Nancy Center - Grand Est
City : Nancy, France
Desired start date: 2023-04-03
Type of contract: 4-year fixed-term contract
Level of diploma required: BAC+5 or equivalent
Desired level of experience: 3 to 5 years
To apply: https://recrutement.inria.fr/public/classic/fr/offres/2023-05788
For more information, contact: [email protected]
Full job description: https://recrutement.inria.fr/public/classic/fr/offres/2023-05788
CONTEXT
This position is part of the Inria COLaF Challenge (Corpus and Tools for the Languages of France), which is a collaboration between the ALMAnaCH and MULTISPEECH teams. The objective of the Challenge is to develop and make available digital linguistic technologies for the Francophonie and the languages of France, by contributing to the creation of inclusive data corpora, models, and software bricks. The ALMAnaCH team focuses on text and the MULTISPEECH team on multimodal speech. The two main objectives of this project are:
(1) The collection of French-speaking, massive and inclusive data corpora: This involves building very large textual and speech corpora, with rich metadata to improve the robustness of the models in the face of linguistic variation, with a particular place for geographic-dialectal variation in the context of the Francophonie, part of which may be multimodal (audio, image, video), or even specific to French sign language (LSF). Data related to multimodal speech will concern, among other things, dialects, accents, the speech of the elderly, children and adolescents, LSF and other languages widely spoken in France.
Corpus collection will be based primarily on existing data. These data (multimodal speech) can come from the archives of the INA and regional or foreign radio-televisions, but rarely in a directly usable form, or from specialists, but in the form of small scattered corpora. The difficulty consists on the one hand in identifying and pre-processing the relevant data in order to obtain homogeneous corpora, and on the other hand in clarifying (and if possible relaxing) the legal constraints and the financial counterparties governing their use in order to ensure the widest possible impact. Where legal constraints do not allow the use of existing data, additional data collection effort will be required. This will probably be the case for children (applications to education) and the elderly (applications to health). Depending on the situation, this effort will be outsourced to field linguists or lead to a full-scale campaign. This will be conducted in collaboration with Le VoiceLab and the DGLFLF.
The development and provision of inclusive linguistic technologies: The linguistic technologies considered in this project by the MULTISPEECH team are speech recognition and synthesis, and sign language generation. Many technologies are already on the market. It is therefore a question of not reinventing these tools, but of making the necessary modifications to them, so that they can exploit the inclusive corpora created. The technologies that will be used in this project include, but are not limited to, the following tasks:
Identification and (semi-)automatic pre-processing of relevant data within existing masses of data. This includes detection and replacement of named entities for anonymization purposes.
Neural architectures and approaches adapted to low-resource scenarios (data augmentation, transfer learning, weakly/unsupervised learning, active learning, and combinations between these various forms of learning)
ASSIGNMENTS
The project engineer will have two main missions:
Project management and practical coordination of the contribution of the MULTISPEECH team to the Inria Challenge. The project lead engineer will work in close collaboration with a "junior" engineer, a researcher and two doctoral students, all working within the framework of this project. He will ensure close supervision of the “junior” engineer and very frequent interaction with the researcher and doctoral students. He will also be in contact with the members of the MULTISPEECH team. There will certainly be strong consultation and collaboration with his counterpart within the ALMAnaCH team.
Data collection and creation of multimodal speech corpora (this includes: certain dialects, accents, the elderly, children and adolescents, LSF and certain languages widely spoken in France other than French). Much of the data collection will be from speaker associations, content producers and any relevant partners for data retrieval. The project engineer will be called upon to discuss, in particular the legal aspects, with our interlocutors.
MAIN ACTIVITIES
Definition of the different types of corpora to be collected (identify potentially exploitable corpora, establish a priority and a collection schedule)
Collection of speech corpus from content producers or any other partner. (ensure that the data respects the norms and quality standards)
Negotiation of data use contracts, ensuring compliance with legal aspects (negotiating data use conditions with content producers or partners, ensuring that intellectual property rights are respected and that legal aspects are taken into account).
Creation and provision of linguistic technologies for the processing of these corpora: once collected, the data must be analyzed and processed in such a way as to extract useful information. The project engineer must propose technologies and tools among the existing ones, necessary for this analysis, and ensure that they are accessible to users.
Close supervision of the junior engineer: support and advice on technical and strategic development choices.
Consultation and animation of exchanges between the members of the project: (1) with the researcher and the two doctoral students (reflections and exchanges on the data, and their adequacy to the Challenge.); (2) coordination with project members within the ALMAnaCH team.
Technological watch, in particular in the field of this challenge.
Writing and presentation of technical documentation
Note: This is an indicative list of activities which may be adapted in accordance with the mission as stated above.
SKILLS
REQUIRED PROFILE :
Degree in computer science, linguistics or any other training in the field of automatic speech or language processing
Proven experience in project management and communication
• In-depth knowledge of language technologies
• Ability to work in a team and meet deadlines
• Good knowledge of English
KNOWLEDGE
• Ability to write, publish and present in French and English
• Mastery of project management and negotiation techniques
• Legal bases (personal data, intellectual property, business law)
EXPERTISE
• Analytical, editorial and synthesis skills
• Know how to support and advise
• Know how to develop a relational network
• Know how to lead different projects at the same time
• Negotiation skills
KNOW-HOW
• Sense of responsibility and autonomy
• Sense of contact and taste for teamwork
• Rigour, sense of priorities and reporting
• Relational qualities (listening-diplomacy-power of conviction)
• Appetite for negotiation (Le VoiceLab, DGLFLF, etc.)
• Ability to anticipate
• Spirit of initiative and curiosity of mind
FURTHER INFORMATION
Full-time position, to be filled as soon as possible.
Remuneration according to experience.
Applications must be submitted online on the Inria website. Processing of applications submitted through other channels is not guaranteed.
ABOUT INRIA Inria is the national research institute for digital sciences and technologies. World-class research, technological innovation and entrepreneurial risk are its DNA. Within 200 project-teams, mostly shared with major research universities, more than 3,500 researchers and engineers explore new avenues, often in interdisciplinarity and in collaboration with industrial partners to meet ambitious challenges. . Inria supports the diversity of innovation pathways: from open source software publishing to the creation of technology startups (Deeptech).
ABOUT THE INRIA NANCY – GRAND EAST CENTER
The Inria Nancy – Grand-Est center is one of nine Inria centers bringing together 400 people, divided into 20 research teams, and 8 research support departments. All these research teams are joint with academic partners, and three of them are based in Strasbourg.
This research center is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative SMEs, large groups, start-ups, incubators & accelerators, competitiveness clusters, research and higher education players, technological research institutes .
WORKING ENVIRONMENT
The project lead engineer will work within the MULTISPEECH project team at the Inria Nancy Research Center. MULTISPEECH's research focuses on multimodal speech, particularly on its analysis and generation in the context of human-computer interaction. A focus of this work is the design of machine learning models and techniques to extract information about linguistic content, speaker identity and states, and the speech environment, and to synthesize multimodal speech. using limited amounts of labeled data.
To apply https://recrutement.inria.fr/public/classic/fr/offres/2023-05788
Title: areal imaging and deep learning for forest assessment
Keywords: multispectral imaging, remote sensing, image processing, deep learning, data fusion, forest.
Context: The forest is one of the richest environments in biodiversity. It constitutes a reservoir and a shelter for fauna and wild flora. The forest helps to stabilize the local and general climate by acting on humidity, temperature and wind. It allows to fight against erosion, avalanches, floods, groundwater pollution, it improves the quality of underground water, reduces the costs linked to the energy necessary for water purification. However, the forest is a fragile environment that is particularly subject to the hazards of climate change. It is therefore necessary to better understand the forest and to act to promote its development and its adaptation to climate change through precision silviculture.
Objective: consists in the development of software tools to recognize and measure from satellite and drone photos, the characteristics of trees, the growth of trees, the impacts of climate change and alert on the risks of dieback. The goal is to propose new methods based on deep learning approaches for multimodal data fusion, namely 3D and multispectral information. Since we face a scarcity of labeled data and a large amount of unlabeled data, we will focus on approaches that combine self-supervised learning with supervised and semi-supervised learning.
Profile: PhD degree with experience in machine learning for analysis of images and data with different modalities.
Duration: ~18 months
Applications: CV to be sent to: [email protected] ; [email protected]
A position (PhD or postdoc level) is available to work with Prof Pascal Meissner in the ‘Center for Artificial Intelligence and Robotics’ at the ‘Wuerzburg-Schweinfurt Technical University of Applied Sciences’ on one of today’s most relevant research problems at the intersection of autonomous robotics, machine learning, computer vision, and artificial intelligence.
Learn as you help robots see, learn, and navigate! As mobile robots spread into different areas of human activity, they are breaking through the boundaries of the structured and static environments, such as houses or gardens, where they were first used. This is particularly thanks to breakthroughs in deep learning, which have provided robots with an unprecedented level of flexibility and safety in navigating complex environments. However, these advances remain limited to environments through which such robots have previously been manually steered to painstakingly record 3D maps of them. Still, we need robots that can explore and monitor unknown environments (without having been steered through them first) to perform tasks in them. Giving robots such capabilities is the goal of this project and of utmost importance for the success of future robotic systems.
CANDIDATE’S PROFILE
We are hiring! Our team is looking for a motivated research collaborator who has
A German Master’s (at 1.8 or above) or Bachelor’s degree (at 1.4 or above), or international equivalent (undergraduate degree with minimum GPA at 3.5 out of 4.0) in either Computer Science, Electrical Engineering, Mechanical Engineering, Physics, Mathematics, or a related discipline. If your degree is not from an EU country, visit (anabin.kmk.org) for guidance
Confidence and independence in programming complex systems (hands-on experience in software development)
Solid background in algorithms and data structures -
Solid skills in maths (skills in statistics are helpful) -
Strong communication skills in English (both oral and in writing)
Interest in autonomous robotics, machine learning, computer vision, or artificial intelligence
We will give you the opportunity to work independently and the freedom to steer the direction of the research according to your interests and strengths within the overall project goal.
FUNDING
The position is fully funded in accordance with the German TV-L salary scale, pay grade : E13, employment: 100 % of standard working time (about 4000 euros per month before tax and social security contributions), see also https://oeffentlicher-dienst.info/c/t/rechner/tv-l/west?id=tv-l-2023&matrix=1
APPLICATION INFORMATION
This position will be filled as soon as an appropriate candidate is found. Applicants are encouraged to contact Prof Pascal Meissner (pascal.meissner[at]thws.de) to discuss their interest. Details can also be found at: https://www.thws.de/forschung/institute/idee/center/cairo/career/phd-position-machine-learning-for-autonomous-robot-exploration
Applications should include:
All Degree Certificates/Academic Transcripts (German, English or officially translated into English). Please indicate your GPA
A full CV describing your background (max 2 pages). Please indicate your relevant skills, scientific publications, awards, research videos and/or code, professional profile(s)
A Research Proposal outlining the extent and ambition of your proposed research, written in English, and using sources and methods from the current literature (1,000 to 1,500 words excl bibliography). It will be assessed for a) evidence of interest in and understanding of the proposed area of research, b) the originality of the proposed research and c) your ability to present a reasoned and coherent case
Any documents providing evidence of academic achievements, relevant practical experience, and qualifications earned at or outside of the university
ENVIRONMENT
You will be supervised by Prof Pascal Meissner (the PhD shall be co-supervised by another university professor, tbd based on the project topic) and will be a part of a cross-disciplinary team. As a member of our team, you will have unlimited access to our state-of-the-art robotics lab, as well as outstanding experts in autonomous robotics, computer vision, reinforcement learning, representation learning, semantic data processing, trustful learning, strong artificial intelligence, and many more. Teamwork, diversity, and transparency belong to our core beliefs.
You will also have the opportunity to contribute to live industrial projects from time to time. In addition, senior research collaborators are encouraged to take up teaching assistantships to develop their teaching skills, should they envision their futures in academia.
CAIRO (Center for Artificial Intelligence and Robotics) is a new research center established at the Wuerzburg-Schweinfurt Technical University of Applied Sciences (THWS) under the Hightech Agenda Bavaria. The Hightech Agenda Bavaria is a technology offensive unique in Germany with a total investment volume of two billion euros. In CAIRO alone, 3.3 million euros are being invested and 8 new professorships created. The city of Wuerzburg is located in Lower Franconia in the northwest of Bavaria. It is a center for education and research and an attractive tourist destination.
Prof. Dr.-Ing. Pascal MEISSNER Professor in Robotics and Artificial Intelligence
Center for Artificial Intelligence and Robotics (CAIRO) Faculty of Computer Science and Business Information Systems Technische Hochschule Wuerzburg-Schweinfurt (THWS)
Franz-Horn-Strasse 2 (room K.1.08) 97082 Wuerzburg +49 (0) 931 35118353
https://fiw.thws.de/fakultaet/personen/person/prof-dr-ing-pascal-meissner/
Our Deep NeuroCognition Lab in NTU and A*STAR, Singapore is currently recruiting 1 PhD student (in collaboration with the University of Manchester) and 3 research scientists.
Research experiences in either of these areas (computer vision, machine learning, neuroscience, cognitive science, and AI) are preferred.
PhD job post: https://www.findaphd.com/phds/project/a-star-human-visual-recognition-inspired-multi-agent-reinforcement-learning-for-drone-search-and-rescue-in-complex-environment/?p155665
Research scientists will receive competitive monthly salaries (estimated 5k - 9k sgd monthly depending on past experiences) and other benefits (e.g. medical insurance, 21-day annual leave, sick leave).
Job posts for research scientists: https://a0091624.wixsite.com/deepneurocognition-1/join-us
If you are interested in applying, please send your CV + research statement to Mengmi Zhang ([email protected]).
Mengmi Assistant professor and PI of Deep NeuroCognition Lab School of Computer Science and Engineering
Nanyang Technological University (NTU), Singapore CFAR and I2R @ Agency for Science, Technology and Research (A*STAR)
Lab website: https://a0091624.wixsite.com/deepneurocognition-1