3DS OUTSCALE France is recruiting an Engineer-researcher in Data Science with a PhD.
If after your PhD degree, you are looking for a position in the industrial sector where you will highlight your scientific know-how, take a look at this announcement: https://fr.outscale.com/poste/ engineer-researcher-in-data- science-f-h/ #recrutement #cloudcomputing
Callau-Zori Sea Datalake Officer
+33 1 53 27 52 70 (ext : 20 12)
319 Hill Offices - 92210 Saint-Cloud
Location and unit: CEA LSPS
Located in the south of France (Marcoule), the Process Simulation and Systems Analysis Laboratory aims at:
- the simulation of processes in stationary or dynamic state.
These simulations aim at defining a process diagram, estimating its performance, sizing the equipment, but also assessing incident scenarios (safety studies) and analysing malfunctions.
- defining process diagrams and carrying out scenario studies, backed by technical-economic evaluations and preliminary waste stream estimates, with a view to guide process choices. The project needs to have close interactions with another CEA entities, CEA ISAS and CEA LIST.
Located in Saclay, south of Paris, CEA LIST (http://www-list.cea.fr/) is a scientific and technological research center dedicated to the development of software, embedded systems and sensors for applications such as defense, security, energy, nuclear power, the environment and health.
Within this institute, the SID (Data Intelligence Service) works on algorithms and methodologies for artificial intelligence and signal processing.
The laboratory's research and technological advances are guided by a variety of applications, for which the specificities and constraints on the data or the execution environment require a fine design of AIs and their integration as the unitary bricks of complex systems.
This entity takes part of this project only to connect it to the neural network developments.
Qualifications 1. PhD in machine learning from an accredited university
2. Excellent communication skills, both verbal and written in English
3. Skills in Python language
4. Communication skills in French
5. Experience in uncertainty estimation
6. Experience in physics application is a plus
Salary & benefits
The salary will depend on the applicant’s profile and experience. The position comes with various social benefits (e.g. health insurance). This position is open for one year.
Application and contacts
To apply send an updated CV and a motivation letter to: Amandine DUTERME ([email protected])
Fabrice GAUDIER ([email protected])
Laurence CORNEZ ([email protected])
The position is open immediately (November 2021).
Review of applications will begin as soon as applications are received and continue until the position is filled or the deadline of January 1st 2022 is reached.
Post-doc: Machine learning technics and knowledge-based simulator combined for dynamic process state estimation
Location and unit: CEA LIST/ SID
Located in Saclay, south of Paris, CEA LIST (http://www-list.cea.fr/) is a scientific and technological research center dedicated to the development of software, embedded systems and sensors for applications such as defense, security, energy, nuclear power, the environment and health.
CEA LIST is part of the dynamic and stimulating ecosystem of the University of Paris-Saclay - the largest French scientific center with 60,000 students.
It has more than 700 researchers focusing on intelligent digital systems, centered around artificial intelligence, the factory of the future, innovative instrumentation, cyber-physical systems and digital health.
Within this institute, the SID (Data Intelligence Service) works on algorithms and methodologies for artificial intelligence and signal processing.
The laboratory's research and technological advances are guided by a variety of applications, for which the specificities and constraints on the data or the execution environment require a fine design of AIs and their integration as the unitary bricks of complex systems.
The project needs to have close interactions with another CEA entity, CEA Marcoule. Located in the south of France, the Process Simulation and Systems Analysis Laboratory aims at:
- the simulation of processes in stationary or dynamic state. These simulations aim at defining a process diagram, estimating its performance, sizing the equipment, but also assessing incident scenarios (safety studies) and analysing malfunctions.
- defining process diagrams and carrying out scenario studies, backed by technical-economic evaluations and preliminary waste stream estimates, with aiming at guiding process choices.
Qualifications 1. PhD in machine learning from an accredited university
2. Excellent communication skills, both verbal and written in English
3. Programmation in Python language (Tensorflow will be used)
4. Communication skills in French
5. Experience in convolutional network using times series is a plus
6. Experience in physics application is a plus
Salary & benefits
The salary will depend on the applicant’s profile and experience. The position comes with various social benefits (e.g. health insurance).
This position is open for one year, renewable once.
Application and contacts
To apply send an updated CV and a motivation letter to: Laurence CORNEZ ([email protected])
Binh DINH ([email protected])
Amandine DUTERME ([email protected])
Stéphane GAZUT ([email protected])
The position is open immediately (October 2021). Review of applications will begin as soon as applications are received and continue until the position is filled.
From: Julien Velcin [email protected]
Hello to everyone, We are looking to recruit a post-doctoral fellow in machine learning to work on textual data organized in a network.
This would be for a period of one year with a start scheduled for early December.
You will find the detailed offer below.
Do not hesitate to forward the offer to people likely to be interested around you.
Best regards, - Julien velcin
Computer science teacher L3 IDS Manager
Coordinator of the HuNIS cluster University of Lyon, Lyon 2, ERIC UR 3083 http://eric.univ-lyon2.fr/~jvelcin
Job offer: Post-doctoral fellow in Machine learning
Starting date: early December
Contract duration: up to 12 months
Place of work: ERIC laboratory (University of Lyon 2, Bron campus)
Working conditions: face-to-face at the ERIC laboratory (if the situation sanitary permits).
Stays of a few days each are planned on the EDF R&D site in the region Parisian (costs covered).
Context : This contract constitutes the central element of the POIVRE project, financed by the IRSDI program of the Jacques Hadamard Foundation ( https://www.fondation-hadamard.fr/ ).
The project involves researchers of the ERIC laboratory and EDF R&D.
Members of the ERIC laboratory, in collaboration with their partners, have been working years on the processing of textual data [1-3] and on machine learning of representations adapted to networks of documents [4-7].
Topic : The POIVRE project aims to build new solutions for analyze the points of view, solutions that will be applied to analysis of debates on Twitter about nuclear power in the countryside French presidential election.
Indeed, this exchange platform is a heterogeneous information network that allows individuals to communicate by posting messages (textual information) via different mechanisms (following relationship or being followed, forwarding the message by ReTweet, like or mention).
However, this type of network is a place privileged exchange of points of view where phenomena of dissemination of information, partisan groups, influence.
The objective of the post-doctoral fellow is to design new methods to analyze points of view as they are frozen in a network heterogeneous information like Twitter.
For this, the main idea consists of using deep learning approaches such as Graph Neural Networks (GNN) by adapting them to different characteristics related to the question from the point of view.
Indeed, this can depend on the position of the node in the graph but also different elements (e.g. arguments) developed in the textual content of the messages.
The methods developed must can be used to identify communities at points of similar view.
The methods developed in this work will in particular be tested on a dataset from Twitter, collected during the campaign presidential election which begins in France.
This dataset will relate in particularly on the debates generated by energy issues (nuclear, renewable energies).
In addition to the support of researchers in Computer Science with experience in machine learning and analysis social networks, the post-doctoral fellow will be able to benefit from the expertise of sociologists specializing in the study of representations on the subject of energy.
Profile expected We are mainly looking for a doctor in machine learning with worked on network data (graphs).
NLP experience would be a real plus, as well as an interest in collaborative work in close collaboration with the social sciences.
At the ERIC laboratory, the post-doctoral fellow will be supervised by Julien Velcin ( http://eric.univ-lyon2.fr/~jvelcin/ ) and Adrien Guille (https://adrienguille.github.io ).
The work is in collaboration with Philippe Suignard and Mathieu Brugidou ( https://www.pacte-grenoble.fr/membres/mathieu-brugidou ) at EDF R&D.
Please send your application to the following address: [email protected]
Your file must include:
- CV
- cover letter
- letter of recommendation (optional)
Company: European Marketing of Grande Distributions SA
Address: 39 rue du Chemin de fer 99137 WALFERANGE LUXEMBOURG
Mail: [email protected]
As part of our activities, we recruit an engineer of research in NLP, with a strong Machine Learning component and Deep Learning.
Description below, for any information, I invite you to contact us contact.
The objective is the development of question-and-answer systems and latest generation chat bots combining deep learning and our clean technologies.
We favor learning approaches to develop our automatic natural language understanding system. This work will focus on the development of solutions based on recent technologies in the field of deep learning.
Job profile:
- Young graduate of a major engineering school, Master of research, Doctorate or graduate of a Master in AI. Specialist Machine Learning techniques and tools dedicated to natural language processing. - You have experience in a field of NLP combining Deep Learning, and you are able to design ready-made models be put into production. (Transfer learning and fine-tuning)
- You are proficient in Python, and in particular the Deep Learning libraries and NLP (PyTorch, Transformers, Fairseq, etc.).
- You have good knowledge of standard NLP systems in Python (ex: SpaCy, Scikit-learn).
- You are comfortable with Linux, Git and Docker.
- You can study, understand, interpret, use, maintain and supplement existing source code.
- You know how to work in a team and invest yourself over time in a big project.
- Appreciated skills: Machine Learning services in the AWS cloud (AWS SageMaker, AWS EC2, AWS Elastic Load Balancing, AWS Lambda and equivalent services on Azure, etc.).
Our team is made up of multiple specialties: doctors and AI engineers, web developers, computer scientists, expert professors in linguistics, linguistics researchers.
Candidacy Please send your application to the following address: [email protected]
Your file must include: - CV
- cover letter
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Other information: Date of hire: as soon as possible.
Remuneration: according to experience
The position will be carried out mainly by teleworking, with a large independence
3-month CDD followed by a CDI.
Hello, Thank you for disseminating this CIFRE thesis offer with Orange Labs on the following subject: Multi-agent simulation for intelligent decision-making in 5G + networks
Details are in the attached document and applications should be sent to Chaima Ghribi ( [email protected] ) and myself ( [email protected] ) before October 20.
Regards, Leila MERGHEM-BOULAHIA
Dear colleagues, We have a two-year postdoc position to fill in the EOS VeriLearn (Verifying Learning Artificial Intelligence Systems) project at the Faculty of Computer Science of UNamur (Namur, Belgium).
VeriLearn is a large project involving 10 academics from three Belgian unversities. Within VeriLearn, the candidate will be integrated in an interdisciplinary team working at the intersection of AI, ML and SE.
The goal of this postdoctoral research is to define, design and evaluate “active testing” (a mix of active learning and software testing) techniques for ML models.
In particular, the successful candidate will analyse automatically the datasets to infer properties of interest in the form of constraints, rank them depending on the desired validation goal and integrate them in testing techniques (metamorphic testing, constraint-guided fuzzing, etc.).
This candidate will work with Prof. Benoit Frénay and Dr. Gilles Perrouin in the Faculty of Computer Science at the University of Namur in collaboration with the KULeuven DTAI group.
More infos on • https://jobs.unamur.be/emploi.2021-09-09.2912866089/view
• https://euraxess.ec.europa.eu/jobs/681147
Deadline: October, 15th, 2021 (11h59 pm AoE). Expected starting date: January 1st, 2022 (negotiable, depending on COVID or candidate constraints).
Please send your application or questions to [email protected] and [email protected].
Best regards,
Benoît Frénay Gilles Perrouin
Dear colleagues, IMT Atlantique in Rennes, France, and Mid Sweden University in Sundsvall, Sweden, offer an opportunity for a co-tutelle PhD position in industrial IoT and cognitive networks.
Subject : Self-Organizing Large Scale IoT Mesh Networks through Distributed Time Synchronization & Cognitive Coexistence
Description : The Internet of things (IoT) industry is expanding faster than ever, increasing the number of connected devices by short-range radio technologies (e.g., Zigbee, Bluetooth, WiFi) to an estimated volume of 20.6 billion devices by 2026 (Ericsson Mobility Report, Nov. 2020). A prominent factor in this growth is the license-free Industrial, Scientific, and Medical (ISM) frequency bands, which are harmonized worldwide for deploying independent networks without licensing. As a result, this growth is not only increasing the number of IoT systems but also the size of systems to support smart applications and their coexistence/interference scenarios in the same environment. Supporting large-scale wireless mesh IoT networks with interference awareness, while not compromising important performance metrics like throughput, latency, and current consumptions, is key to meet the emerging connectivity demands of smart spaces (e.g., offices, industries).
One of the favorite channel access methods for IoT used in smart commercial or industrial buildings is Time Slotted Channel Hopping (TSCH)-enable mesh networks. TSCH enables the robustness of IoT networks against interference by implementing Adaptive Frequency Hopping (AFH), both being integral to operate in crowded license-free frequency bands. However, TSCH technology requires accurate network-wide time synchronization for synchronous AFH, which becomes a challenge with network size/scale.
Apart from AFH, time synchronization is central to executing distributed control and sensing for the underlying applications (e.g., data fusion, event localization). Meanwhile, AFH requires intelligence on coexisting technologies; estimation and prediction of spectral footprints in time, frequency, and space domain of RF interference play a vital role in increasing the robustness and dependability of TSCH systems by blacklisting the interfered radio resources. In this context, this project will contribute towards designing dependable large-scale low-power wireless mesh networks, with two crucial research elements on establishing and maintaining such networks as:
Developing scalable and accurate distributed time synchronization schemes for expanding IoT systems.
Instead of a statistical model for existing reactive AFH schemes, developing proactive AFH, based on radio-map generation with interference detection and learning, to increase reliability and ability to coexist with other IoT systems.
Keywords : IoT, Industrial Networks, Industrial IoT, Mesh Networks, Wireless Networks, Time Synchronization, Cognitive Networks.
Environment : The candidate will work at the SRCD department of IMT Atlantique, Rennes (the first two years), and at the STC research center of Mid Sweden University in Sundsvall (the last two years). The working language will be English. The expected startup date is November 1, 2021, but may however be flexible.
Required competence for the applicant :
Signal processing, especially detection and estimation theory for developing clock offset and skew estimators, and interference detection, inference, and radio maps generation.
Applied mathematics and optimization for clock stability analysis and parameter optimization.
Embedded system programming for developing and demonstrating the developed components as a system.
Good understanding of IoT protocol stacks, PHY/MAC layers, and real-time operating systems (e.g., Contiki, FreeRTOS, TinyOS).
How to apply and/or get further information :
Applicants must submit an official academic transcript of records for their bachelor and masters education. It is a requirement to hold a masters or an equivalent degree for being considered for this position. At least two references (name, position, e-mail, and telephone number) should be included in the application. Candidates should send by e-mail a CV and a statement of purpose to:
Georgios Papadopoulos - IMT Atlantique, Rennes campus [email protected]
Nicolas Montavont - IMT Atlantique, Rennes campus [email protected]
Mikael Gidlund, Mid Sweden University [email protected]
Aamir Mahmood, Mid Sweden University [email protected]
It will be greatly appreciated if you forward this position to whomever might be interested.
We are looking forward to strong applications.