Postdoctoral fellow positions in deep learning for protein-protein interactions – Royal Institute of Technology (KTH) and Stockholm University (SU) in Stockholm, Sweden

Come work with us to develop state-of-the-art deep learning techniques to push the boundaries of structural biology. Key areas of deep learning research include, but are not limited to attention-based models such as transformers, memory augmented modeling, transfer learning techniques such as knowledge distillation, and self-supervised contrastive learning in the context of protein folding and interactions between multiple proteins.

Sweden has excellent living conditions where work-life balance is of great importance. Stockholm has the second highest number of unicorn startups right after Silicon Valley.

The position’s salary will be competitive and decided upon agreement. Latest postdoc salary statistics at KTH can be found here: https://intra.kth.se/en/anstallning/anstallningsvillkor/lon/lonerevision-1.838777

The deadline for the postdoc fellow applications is Jan 31, 2022 11:59 PM CET. Read more and apply here:

KTH position: https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:457741/where:4/

SU position: https://www.su.se/english/about-the-university/work-at-su/available-jobs?rmpage=job&rmjob=16725

We strongly encourage you to apply! If you have any questions, feel free to contact me at azizpour[at]kth.se

The ANR MOBILES project aims to document, understand and support spatial practices and language learning for international students hosted in higher education in France.

The originality of the project consists in analyzing the learning that the immersion stays conceal potentially through the prism of spatial practices augmented by digital tools.

This is (1) to analyze the spatial practices of the students, that is to say to uncover the opportunities learning that the context conceals;

(2) to design a map of the city as it is practiced, thanks to a cartographic interface allowing to combine heterogeneous sources of both quantitative and qualitative data and their exploration;

(3) to study in what ways recommendation systems based on user participation can be implemented in order to to support learning goals.

Missions

Part of the MOBILES project consists of:

(1) developing innovative methods to collect traces of activity (explicit and declared), which are produced by various and geolocated sources (photographs, social networks, route research ...);

(2) design modeling methods, analysis and visualization, combining qualitative methods with formalized methods in computer science and geomatics.

A prototype smartphone application will be developed to allow the project team

(1) to collect digital data relating to individual activities (geographical traces, traces digital activities including annotations produced) and

(2) to provide a visualization mapping of these traces and an

(a) individual,

(b) shared and

(c) collective discussion. To achieve this objective, the raw traces (containing “obsels”, that is to say the elements observed [Champin et al., 2013]) will be the starting point for modeling the data and constructing visualizations considered usable and acceptable by the participants.

The missions of the recruited person will therefore be to produce:

• technical specifications for the smartphone application (study of uses, definition of

activity indicators, in agreement with the members of the project);

• the definition of a model of collected traces

• the first iteration of the application prototype

Work context

The recruited person will join the TWEAK team of the LIRIS laboratory, located on the Doua campus in Lyon-Villeurbanne and will work under the direction of Marie Lefevre. She will be in contact with the various partners of the project:

• At the ICAR Language Sciences laboratory (UMR 5191): Jean-François Grassin, Justine Lascar and Emilie Magnat. The project is based on their expertise in the uses of digital technology in the framework of learning practices and EES.

• At the LIRIS IT laboratory (UMR 5205): Nathalie Guin and Béatrice Fuchs. The LIRIS brings his skills to the collection of modeled traces, the analysis of traces to develop learning indicators, the design of systems based on the use of traces and recommendation systems.

• At the EVS Geography Laboratory (UMR 5600): Claire Cunty, Dominique Chevalier, Thierry Joliveau and Hélène Mathian. EVS brings its skills to the analysis of site practices, in their geographic and sensitive dimensions, as well as on the uses of interfaces digital cartography, both in terms of acquisition in a contributory context and of individual and collective visualizations of local practices.

The CDD is for 12 months, and will begin as soon as possible.

Expected skills

• Holder of an engineering degree or master's degree in computer science with solid experience in Web development

• Good technical skills in web and mobile application development

• Knowledge of semantic web standards (RDF, OWL) and in particular those related to learning trace analysis (xAPI, LRS) • Experience with the Git code manager tool and documentation skills

• Respect of deadlines, rigor, organization, ability to work in interaction with teams remote, researchers, teachers

Application procedures

Candidates are invited to submit a CV of 2 to 3 pages, with a cover letter and possibly letters of reference, in PDF format to [email protected].

The CIAD laboratory in Dijon is recruiting a postdoc for 12 to 18 months depending on profile as part of the ANR DALHAI project.

The objective of this project is to develop compact all-optical arithmetic and logical units (ALUs) exploiting the spatial and spectral distributions of 2D confined plasmon modes in planar cavities carved from ultrafine Crystals of Au or Ag. We initiated the development of a new modeling approach by combining generative antagonist network (GAN) approaches and logical reasoning to perform optical simulations and obtain experimental data. The goal of this hybrid reasoning environment is to propose device geometries and excitation protocols to solve the reverse design of complex reconfigurable ALU. Nanofabrication, simulations, optical benchmarking, exploitation and reconfiguration of ALU proposed by AI will make it possible to physically build these ALUs. The experimental manufacturing and optical tests and numerical simulations of plasmonic ALU will be carried out by the ICB (CNRS, Dijon).

The results obtained open up a new and very innovative artificial reasoning path that we wish to explore with this post-doctoral position. The mission is spread over several phases. 1/ The first phase revolves around the AI approach put in place. This phase consists of analyzing the limitations of simulation tools in the field of plasmonics and nanophotonics and becoming familiar with the AI approach implemented. 2/ The second phase aims to automate the generation of a corpus of synthetic data by implementing the hybridization of artificial intelligence algorithms. 3/ The third phase of this post-doctorate consists in setting up symbolic and connectionist artificial intelligence approaches to solve problems applied to the field of nano-plasmonics such as the prediction of optical signals and the optimization of the efficiency of logic gates

The position is open for a start hoped in February 2022 over a period of 12 months to 18 months depending on the profile of the candidate.

The place of activity is the CIAD laboratory - University of Burgundy, 64 rue de Sully, 21000 Dijon

The salary is about 2500 euros gross per month.

This position is open to anyone with a PhD in Computer Science with good experience in machine learning/deep learning and possibly Semantic Web technologies. Fluency in written/spoken English is also required. A good publication record and strong programming skills will be a plus. Applications will be accepted until the position closes. Applicants must send a full CV including a full list of publications, a cover letter stating their research interests, achievements to date and vision for the future, as well as letters of support or the names of 2 people who have worked with them.

Contact: Christophe Nicolle ([email protected])

Thank you for your help in disseminating this offer.

NLP and deep learning against pandemics* (2 year postdoc) Collaborative project "ComCorText"

*Keywords:* NLP, AI, deep learning, epidemiology, risk factors, outbreak detection.

*Host lab**:* Imaging and Modeling Unit https://research.pasteur.fr/en/team/imaging-and-modeling/, Institut Pasteur (https://www.pasteur.fr/en), Paris, France

Collaboration with the Epidemiology of Emerging Diseases Unit https://research.pasteur.fr/en/team/epidemiology-of-emerging-diseases/ (Institut Pasteur) and Sanofi

The COVID-19 pandemic has abundantly illustrated the importance of quickly identifying the factors that increase or decrease pathogen transmission. An early understanding of the airborne nature of SARS-CoV-2 transmission, for example, could have helped slow down the pandemic and reduce its human burden. In this project, we will explore the potential of natural language processing (NLP) methods to automatically identify risk factors and protective factors by analyzing large corpora of unstructured text.

This project takes advantage of the unique resource provided by the ComCor study, which contains free text descriptions of suspected circumstances of contamination from >50,000 individuals tested positive for COVID-19, totaling well over 500,000 words. The proposed project will mobilize state-of-the-art NLP techniques based on deep learning, such as contextualized word embeddings learned by transformer models (e.g. BERT).

Methods developed in this project will be tested and validated primarily (but not exclusively) on the ComCor data set in collaboration with the Epidemiology of Emerging Disease Unit of A. Fontanet.

Once validated, we will also explore applications of these methods to other text data sets, including social media and data obtained in the framework of the AIOLOS project. AIOLOS is a French-German research program, that aims at supporting decision-making by integrating information from various sources to detect early signs of a new outbreak, monitor its spread and derive appropriate response measures.

A total of 17 partners (5 main partners, including Sanofi and Fraunhofer and 12 associated partners, including Institut Pasteur) are involved in this project.

*We are looking for a highly motivated and autonomous candidate with a solid background in NLP or related fields to lead this project.* Please send applications (motivation letter + CV with names of 2-3 references) to Ch. Zimmer ([email protected]) and Tiffany Charmet ([email protected])

1. Organizational context The World Intellectual Property Organization (WIPO) is a specialized agency of the United Nations. It is dedicated to developing a balanced and accessible international Intellectual Property (IP) system. As part of its mandate, WIPO translates Patent applications and disseminates information about published patent applications using the PATENTSCOPE search engine (https://patentscope.wipo.int/). To make this information available worldwide, WIPO is looking for machine translation (MT) techniques to help the translation of patents in various languages. Our “Wipo Translate” tool is publically available at: https://patentscope.wipo.int/translate. WIPO Translate is also used in other contexts, e.g. translate conference meetings.

In WIPO Translate, we give preference to machine learning approaches; we try to create translation models learning from the data. The final goal is always to provide the best MT in production in term of quality (quality should be competitive compared to commercial tools), efficiency (we target quick translations, less than two seconds for one sentence) and scalability (we train our translation models on world class data in 12 different languages).

WIPO is looking for a research and development fellow who could work on improving our WIPO Translate tool focusing on Neural Machine Translation (NMT). WIPO Translate is based on open source tools, relying mainly on NMT tool Marian.

Neural networks being an emerging field, we are looking for a highly motivated person skilled in Machine learning and Natural Language Processing (NLP) in general. We focus on applied research: applying the latest research development into production.

The WIPO Global Databases Division is working in the area of automatically translating intellectual property documents, mainly patents (see http://patentscope.wipo.int/translate) but also other types of documents (WIPO Translate has been used in other international organizations). WIPO is especially looking for a candidate(s) that could contribute to keep WIPO's “advantage” in machine translation.

2. Duties and responsibilities

NMT

- Knowledge of neural network technologies (deep learning) to experiment with the next generation of MT,

- Ability to experiment with various techniques for setting the best parameters for specific language pairs, specific domains, and for combining various input source corpora (mixing in-domain small corpus with larger out-of-domain corpus), mixing multi languages in a single NMT model etc.

MT-evaluation/benchmarking/quality estimation

- Work on specific tools allowing a reliable automatic evaluation of NMT models (allow for quality comparison between two MT engines)

- Use feedback from human evaluation to further improve our engines (and our automatic metrics)

- Explore and develop tools to provide quality estimation metrics associated with NMT output (use human feedback to improve these metrics)

MT-integration/ Natural language processing

- Work on specific tools allowing a better integration of NMT in the user environment (batch translating texts/ documents/ HTML page),

- Design Graphical User Interface (good knowledge of Java, Jquery and/or Web/JSF 2.0 would be an advantage) to improve means for accessing the output of machine translation,

- Pre- and Post-process texts in different languages to improve translation quality (especially for Chinese, Korean, Japanese and German), e.g. replacing named entities by placeholders, normalizing casing, automatic filtering parallel texts, etc.

Develop methods to collect and clean training data

- Especially on parallel patent sentences (e.g.: filter/clean Patent titles and abstracts, align full texts using patent priority data, etc.), but also on other types of parallel documents (aligning/filtering diplomatic documents etc.),

- Work on combination of various sources for augmenting training data

- Use human post editions,

- use other corpora,

- use synthetic data,

- Define a workflow for updating NMT models using newly published documents (e.g. incremental training, explore online learning algorithms…)

3. Requirements

- Education

- Advanced university degree in Information Technology.

- Experience

- Essential

- At least one year of experience in the field of Machine Learning (R&D projects or PhD can be considered as experience)

- Desirable

- A specialization in machine learning techniques

- Familiar with computational linguistics

- Experience in implementing Machine Learning projects and/or making significant scientific contribution in Machine Learning.

- Job-related competencies

- Essential

- A strong knowledge of programming language is required (Java and/or Python).

- A good knowledge of Unix is required

- Desirable

- Statistics: automatic document classification approaches (Neural Networks, Naive Bayes, SVM, Knn, EM, ANNs, …)

- Web/Internet technologies: Java, Tomcat, JavaScript, Jquery, Angular.js, Jsf, CSS, HTML 5…

- Scripting languages: bash, Python, Perl

- Unix: Ubuntu, Red Hat, configuring Unix remote servers (using command line mode)

- Experience with version control systems (SVN and/or GIT)

and deployment strategies (docker, cloud servers, virtual machines etc.)

- Ability to write user guide, administration documentation and reports in English.

- Excellent decision-making and problem-solving skills.

- A proven background in research (scientific publications) will be a strong plus.

- Search engines: Lucene / ElasticSearch / Solr

- XML technologies

- Databases: nosql techniques, Mysql, Oracle…

- Language skills

- Excellent knowledge of written and spoken English or excellent knowledge of written and spoken French and good knowledge of English.

- Knowledge of other official UN languages would be a plus. A working knowledge of other official languages of WIPO (German, Spanish, French, Portuguese, Russian, Arabic, Chinese, Japanese or Korean) would be an advantage.

4. Organizational competencies 1. Communicating effectively.

2. Showing team spirit.

3. Demonstrating integrity.

4. Valuing diversity.

5. Producing results.

6. Showing service orientation.

7. Seeing the big picture.

8. Seeking change and innovation.

9. Developing yourself and others.

5. Terms and conditions

a) Term of fellowship: up to 12 months, with the possibility of renewable up to an additional 12 months, for a maximum of two years.

b) Anticipated Start Date: March 15, 2022

c) Location: WIPO Headquarters, Geneva, Switzerland.

d) Stipend: is set in accordance with the level of qualifications and experience of the Fellow (stipend starts from 5000 CHF/month).

e) Travel expenses: one economy class ticket (return) from/to the Fellow's place of residence by the most direct and economical route to/from Geneva. If necessary, WIPO may provide assistance in obtaining an entry visa to Switzerland.

f) WIPO provides medical and accident insurance coverage during the course of the fellowship.

g) WIPO will request a “carte de légitimation” for the Fellow, which serves as a residence and work permit, from the Permanent Mission of Switzerland to the United Nations Office and to the other international organizations in Geneva. Family members of the Fellow are not eligible for a “carte de legitimation.”

h) Tax and social security: Fellows shall be solely responsible for meeting any taxation and social security obligations that may arise directly or indirectly from their contract with WIPO.

Additional information

Fellows are not staff members of WIPO and the position does not lead to any employment rights and entitlements beyond the terms of the fellowship.

How do I register my interest?

Expressions of interest, formulated through a brief statement by the candidate addressing each of the requirements set out above, accompanied only by a full curriculum vitae (résumé), should be sent by email to: [email protected] by February 8, 2022.

Only those candidates who are shortlisted for a written test or an interview (via videoconference) will be contacted.

Note for PhD students: WIPO cannot provide academic support for supervising a PhD, a special agreement with a local supervisor can be obtained.

Hello, Please find attached the following 2 internship offers:

1) "Designing and implementing deep learning architectures to predict cohesion's dynamics in small group interactions from multimodal data"

2) "Social Signal Processing of small teams' behaviors in a Virtual Reality environment" Please forward it to those who may be interested.

Role

This is an exciting opportunity for you if you are interested in engineering and/or research. We have many directions to explore. Some tasks are more practical than the other and we will discuss your interests to find the best fit.

The intern’s tasks include but are not limited to:

1) Reviewing literature on small teams acting in eXtended Reality, more specifically in Virtual Reality

2) Computing multimodal behavioral features of cohesion from a new multimodal (audio and motion capture) challenging dataset

3) Data analysis

2) Working on a computational model of cohesion.

Candidate profile

The ideal candidate should have a strong background on Computer Science, AI, Information Technology, Applied Mathematics or closely related fields.

In addition to a passion for science and programming, the candidate should be open to approach and solve the issues linked to Human-Computer Interaction.

The following skills are also expected:

Good command of English (written and spoken). French language is not a mandatory requirement

Interest in multidisciplinary research at the interface between Computer Science and Sociology/Psychology

Proof of Excellent student career

Strong programming skills (e.g. C++/Python)

Very good communication skills, commitment, independent working style as well as initiative and team spirit.

Offer

Starting date: as soon as possible.

Salary

Full-time intern fellowship according to the Telecom Paris salary scale.

Application deadline

The evaluation of the candidates starts immediately and it will continue until the position is filled.

Application

To apply please send by email to [email protected] and [email protected] in a single pdf file:

A cover letter stating your research interests and how they could be related to the research topic the internship focuses on.

A detailed CV

Transcripts of student records of your last year.

For any additional questions about the position, please contact Prof. Giovanna Varni and Lucien Maman.

Please quote “Intern_position_SocialSignalProcessing_and_VR” in the email subject for both asking information and application.