The DUKe (Data User Knowledge) team of LS2N (Laboratoire des sciences du numérique de Nantes), UMR CNRS 6004 (https://www.ls2n.fr) and chekk (https://www.chekk.me) are launching a call for applications for a CIFRE doctoral position in the field of knowledge graphs and machine learning.
Title: Integration of semantic knowledge into a graph diving approach for improving the quality of knowledge graphs
Keywords: Entity resolution, Knowledge graph, Machine learning, Deep learning, Graph diving, Ontology.
Minimum Bac+5. Possess a doctorate or master's degree in the field of computer science.
Previous experience working on projects is strongly sought after. Master in English.
Duration: 13 months renewable (42 months in total) Job opening: September 2022
Salary: civil service grid
Application methods
Job Information For more information on the position, do not hesitate to contact Mrs. Marie-Pierre Gleizes: [email protected]
Sending applications
CV and motivation letter to be sent to the following address:
Job title: Creation of a data warehouse for the integration of antimicrobial resistance data
Duration of the contract: 3 years
Required degree: Master's degree or PhD in Computer Science
Job description This position is offered as part of a research project (Promise, https://pro.inserm.fr/wp-conte nt/uploads/2021/12/brochure-PROMISE.pdf) whose objective is to create a data warehouse to integrate data from project partners related to antimicrobial resistance.
The development of the data warehouse will be carried out in collaboration with the Zénith team of the National Institute for Research in Digital Science and Technology (Inria).
The Zenith team, an expert in scientific data management, has a solid experience in processing large amounts of data produced by different methods.
The main activities of the recruited person are: • Design a data warehouse to store large volumes of data.
• Exchange with partners to best establish the meaning and possibilities. questioning the data, in particular by crossing them with those of other partners.
• Integrate partner data into the data warehouse. • Create web pages to view query results and update data.
Technical skills and level required: • Knowledge of NoSQL data management systems, in particular MongoDB or Cassandra. • Knowledge of website development.
Gross Salary Between 2500 and 3800 Euros gross monthly (depending on the candidate's experience).
Place of work Zenith team, Montpellier
Contact Reza Akbarinia: [email protected] Florent Masseglia: [email protected]
Profile requested: A master's degree or equivalent in computer science, artificial intelligence or other related specialty
A very good level of mastery in object-oriented programming is necessary (Java, C#, Python) Knowledge of multi-agent systems, machine learning, Internet of Things will be appreciated
Fluency in French (oral and written) required Fluency in English (oral and written) is required
Places of practice: Kardham Company in Paris and CIAD Laboratory in Belfort
Funding: 3-year fixed-term contract with Kardham according to the terms
CIFRE-type financing. Salary €40k to €60k to be negotiated with Kardham.
File to be sent as soon as possible Estimated start of the thesis contract: September 2022
Possibility of having an internship or a fixed-term contract before official recruitment in September 2022.
Applications: Applications should be sent by email to: Prof. dr. Stéphane GALLAND [email protected]
Dr. Emmanuel DUFRASNES [email protected] Dr. Nicolas COCHARD [email protected] Mr Pascal ZERATES [email protected]
The application file must contain: a detailed CV a copy of the Master's degree or any document attesting to the Master's level a copy of the Master's transcripts
Copy of identity card or passport a letter of motivation, references and/or one to two letters of recommendation Incomplete applications will be rejected.
A thesis offer on the characterization of housing / buildings in relation to associated regulatory constraints is to be filled at the UBFC (Univ. Bourgogne Franche-Comté) and the LIB (Laboratoire d'Informatique de Bourgogne).
Thesis title: AI approach for the characterization of housing/buildings in relation to a type of disability and associated regulatory constraints
Host laboratory: LIB - EA 7534, 9 avenue Alain Savary, 21000 Dijon, FRANCE - https://lib.u-bourgogne.fr/
Specialty of the doctoral program prepared: Computer Science
Tagged Artificial Intelligence (AI), Symbolic AI, Ontologies, Logical Rules, Reasoning, Machine Learning, Data Science
Context: The Disability Act of 2005 introduced the obligation to make buildings open to the public accessible by 2015, a deadline postponed to 2024, as part of the "accessibility master plans - programmed accessibility agenda". Since 2017, disability has been one of the priorities of the French government. The progress report published in May 2021, outlines several key actions, including "Developing innovative and inclusive housing solutions" and "Engaging society towards universal accessibility". It is in relation to these two actions that the work envisaged in the context of this thesis is inscribed. The idea is to propose a characterization of a dwelling or a building in relation to regulatory constraints e.g. presence of showers without jump in a new construction from January 1, 2021.
For the past decade, the dematerialization of all data and processes concerning buildings has been a global challenge. At the national level, the latest plan in this area is the BIM 2022 plan - this plan plans to generalize the use of digital and BIM (Building Information Modeling) approaches in the construction sector. The digital transformation of the targeted building leads to a generalization of the use of the digital model by project owners.
Several international standards already exist for the numerical modelling of buildings and urban spaces, including the IDM (Information Delivery Manual (ISO 29481-1:2016), the MVD (Model View Deifnition (ISO 29481-3:2010) and the IFC (Industry Foundation Classes) (ISO 16739:2018). The latter standard is an open standard, used for the representation of all the constituent elements of the physical building. The IFC standard allows the syntactic interoperability of tools and processes around the digital model. Thanks to this object-oriented representation, the IFC makes it possible to uniquely identify each element within a digital model given by a global identifier (called GUID for Globally Unique IDentifier) and to associate the elements with each other in the form of a graph. The IFC model aims to cover the entire life cycle. Therefore it is very rich in order to be able to adapt to the evolution of the digital model and allow the enrichment of the information exchanged. It has been adapted into ontology in the form of ifcOWL [1].
However, the different processes that can be implemented on the basis of these standards still depend heavily on human operators. In addition, the various evolutions undergone by the IFC model have not helped to make it more understandable or to facilitate its manipulation by professionals in the field. In relation to this, several scientific publications have demonstrated the advantages brought by the so-called "Semantic Web" technologies, for the verification of digital models, particularly in terms of accessibility [2][3].
Work envisaged: The research carried out within this thesis will address and combine the two axes of Artificial Intelligence: on the one hand statistical approaches [4] e.g. unsupervised learning from corpora of regulatory texts, and, on the other hand, symbolic approaches [5] e.g. creation of logical rules to identify possible non-compliance with a digital model of housing.
This thesis aims to propose, formalize, specify and then implement an approach allowing a coherent, complete and semantic interpretation of a building and / or housing in relation to existing regulations in terms of accessibility and disability.
In particular, the aim is to study how legislative texts can be adapted in the form of logical rules that can be used to check whether possible non-conformities are presented in digital models of buildings and/or dwellings. A first step aims to extract semi-formal rules from regulatory texts, using machine learning algorithms. In a second step, a knowledge base for buildings/dwellings and accessibility constraints will be designed. The third step aims to translate the rules obtained in the 1st step into a formal language (e.g. SHACL) and apply them to the knowledge base of step 2. Thus, the content of the database can be classified according to the rules and points of non-compliance identified. To facilitate interaction and the addition of new rules, a 4th step aims to implement the knowledge base on a triplet store and allow its query via queries (adapted from the rules). The processing of these requests can be optimized. The approach will need to be extensible to allow for the addition of new constraints or knowledge.
Requested profile: Applicants must hold a Master 2 or an engineering degree in computer science or applied mathematics, related to one of the following fields: artificial intelligence, knowledge engineering, machine learning, natural language processing.
Candidates must have a good level in French and/or English (min. C1 level). Applicants must have an interest in research, a strong scientific background, programming skills.
Constitute a plus of the skills in knowledge engineering (Semantic Web, ontologies), BIM and / or data science.
Start and duration (planned): September-October 2022, 36 months
Funding: Bourgogne Franche-Comté Region File to be sent by 30/05/2022
Audition period: over the water
Description in English: https://euraxess.ec. europa.eu/jobs/776828
we propose a thesis in computer science on combinatorial optimization through speculative research.
This thesis will take place in Lens within the CRIL (University of Artois). Interested candidates are kindly requested to contact me.
More information is available at this address: https://www.adum.fr/as/ed/ see proposal.pl language=&matricule_prop=40245&site=stsupjv
Application deadline: May 13, 2022, 13:00 CEST
A three-year Doctoral Fellowship on extracting information from clinical data documents in a multilingual perspective is offered by the PhD Programme in Brain, Mind and Computer Science (BMCS, http://hit.psy.unipd.it/BMCS) at the University of Padua, in collaboration with the Research Unit Natural Language Processing (https://ict.fbk.eu/units/nlp/ ) at the Fondazione Bruno Kessler (Trento, Italy), where most of the research activities will be carried out. The language of the doctoral program is English.
The application deadline is: 13 May 2022, 13:00 CEST
For more information, the call and applications, see: http://hit.psy.unipd.it/BMCS/admission
The candidate will have the unique opportunity to explore different areas (Natural Language Processing, Machine Learning, Health & Health & Well-being) being directly coached by highly experienced teammates. The PhD involved will work in an international environment at the Fondazione Bruno Kessler (Trento, Italy).
The Fondazione Bruno Kessler is an internationally renowned research company center, whose information technology department ranks first among engineering and information science research centers in Italy.
The Natural Language Processing Research Unit (https://ict.fbk.eu/units/nlp/) is a well-known internationally known research group focused on text mining (information extraction and ontological settlement from text, analysis of feeling and emotional content of texts); conversational agents (task-oriented dialogue systems, questions and answers, persuasion generation messages); and the development of linguistic resources, particularly for the Italian language.
To get in touch with the NLP research unit and discuss the opportunities of this call, contact Alberto Lavelli ([email protected])
The doctoral program in Brain, Mind and Computer Science (BMCS) emerges from the close collaboration between professors of psychology, cognitive neuroscience and information sciences around the unifying theme of human-machine interaction. Its programme is based on the assumption that the ability to work in groups with people from different backgrounds is now a fundamental condition for producing scientific excellence and developing innovative skills that can be used in the labour market.
Required/Preferred Skills and Competencies of the Candidate **** The Candidate must possess basic knowledge of natural language processing and machine learning techniques (especially architectural deep learning).
Experience with biomedical/clinical data would be a plus. Basic programming skills (e.g. Python) would complete the profile.
Fluency in English is required, a basic knowledge of Italian preferred.
Interested candidates are invited to apply by following the instructions given in
https://pica.cineca.it/unipd/dottorati38
before 13 May 2022, 13:00 CEST
For more information, please contact: Alberto Lavelli ( [email protected] )
a team from the University of Hamburg is looking for a post-doc for 3.5 years on "Similarity Measurement of Visual Patterns in Written Artefacts".
I would therefore like to forward this request, which is available here: https://www.uni-hamburg.de/ stellenangebote/ausschreibung. html?jobID=f160068e2df66bbeadfb678c419e1a33e29ea56c
Please contact Mohammed, Hussein Adnan ([email protected]) with any questions.
Detailed description in English:https://selexini.lis-lab.fr/ jobs/2022/03/29/engineer-position
Duration: 12 months
Start: June 2022 (adaptable)
Application: before May 2, 2022 by email to carlos.ramisch [AT] lis-lab.fr
Location: LIS, TALEP team, Aix Marseille University, Luminy campus, Marseille
Remuneration (CDD): €1,600 to €2,000, depending on experience
The objective of the ANR SELEXINI project is to develop original methods of lexicon induction in automatic language processing The lexicons produced by clustering will bring together occurrences of words according to their meanings, but will also contain polylexical expressions, frames semantics, argumental structure, generated definitions, etc. Lexicon induction methods will rely on neural language models (e.g. FlauBERT, CamemBERT) and existing lexical resources (e.g. Wiktionary).
The recruited engineer will be responsible for setting up the initial infrastructure of the project, both in terms of data and tools. The mission will take place in 5 stages: (1) preparation of a large raw corpus representative of various registers of written French, (2) pre-processing of the corpus using parsers, etc., (3) extraction and structuring of the entries of the French Wiktionary, (4) adaptation (fine-tuning) of language models on the corpus of the project, (5) alignment of polylexical words and expressions extracted from Wiktionary with the occurrences of the corpus.
Profile * Master or thesis in a field related to automatic language processing * Notions of French and English * Interest in languages and familiarity with language technologies
Application Send your CV and a few lines explaining why you are applying to carlos.ramisch [AT] lis-lab.fr before May 2, 2022.
You will find in PJ a co-supervised thesis topic, proposed by IMT Atlantique and Polytechnique de Montréal, for which we are looking for a candidate.
Thesis title: Counting and sampling of solutions for anytime pattern discovery
Application deadline: 06/05/2022
Applications should be sent to: [email protected], [email protected], charlotte.truchet@univ-nantes. fr
If you are interested, please send us the following as soon as possible (and before 06 May):
Detailed CV, cover letter, transcript details (including M1 and M2),
elements of bibliography or personal achievements related to a research activity (e.g. master's project, research internship subject, etc.), 2 to 3 letters of recommendation.
Please distribute this attached document to your students and colleagues who may also be disseminating.
As part of this thesis, we are interested in the development of optimization algorithms allowing to define the optimal design of the maritime network.
The central problem that will be studied is known in the literature as of “Liner Shipping Network Design Problem” (LSNDP) [1, 2, 3], which is an NP-hard problem.
First, it will be necessary to understand the various operational constraints and business rules provided by the industrial partner (in this case CMA CGM).
A review of the state of the art will be conducted in order to analyze the different models and resolution approaches proposed and to study their adequacy with regard to the problem posed in the project context.
Ultimately, the objective is to define the model(s) making it possible to integrate all the objectives, constraints and business rules.
These models can be expressed using different formalisms from, for example, constraint programming [4] or integer linear programming [5].
In a second step, from the proposed models, it will be a question of developing algorithms of resolution all taking into consideration reduced execution time objectives and compatibility with operational needs.
Solving algorithms can be based on exact approaches (linear programming, column generation, etc.), approximate methods of the metaheuristic type or hybrid methods.
Location: University of Aix-Marseille, Faculty of Sciences, Computer Science and Systems Laboratory (COALA team), Marseilles
Management : — Djamal Habet [email protected] (co-director) — Cyril Terrioux [email protected] (co-director) — Hamza Ben Ticha [email protected] (co-supervisor) — Salem Ben Ramdane [email protected] (co-supervisor) Start date: September 2022
Remuneration: The monthly salary will be around 1,600 e.
Profile sought: The person sought must hold a Master 2 or an engineering degree with solid computer skills (especially in algorithms and programming), artificial intelligence, programming by constraints, combinatorial optimization and/or operations research. Modeling expertise will be a plus.
Deposit application : The documents required for the application are as follows: — CV (at most 3 pages), — Transcripts, results and rankings of the Master's degree or equivalent (first and second years),
- Cover letter, - Letters of recommendation.
Applications must be submitted before June 15, 2022 in the form of a single pdf file sent by email to Cyril Terrioux ([email protected]).
Computer Science Laboratory of the University of Le Mans (LIUM-EA 4023) offers a thesis on the design and operationalization of collaborative educational activities in virtual reality.
Thank you for spreading this proposal widely around you.
Applications must be sent to Lahcen Oubahssi [email protected] before 20 May 2022.
The application must include: a CV, a letter of motivation,
Master 1 and Master 2 transcripts (those available)
the report of the Master 2 internship (if available)
letters of recommendation.
Type of employment contract: CDD or post-doctorate (depending on profile)
Type of employment contract: Private law
Duration of the employment contract: 2 years (1 year renewable once)
Administrative delay for the start of the contract: approximately 3 months
Job location: Saclay (Ile-de-France)
Send CV and cover letter to: Aurélien Mayoue ([email protected]) Feirouz Ksontini ([email protected])