Hello, Here is the message to broadcast on to [email protected] .
thanks in advance Guillaume GALLOU
24-month IA / CDD research engineer
Development and implementation of innovative AI methodologies for manufacturing applications (defect control, etc.).
Located in Palaiseau (91), in the heart of the scientific environment of the University of Paris-Saclay, the CEA LIST's mission is to carry out technological developments of excellence on behalf of industrial partners. Carrier of the economic and societal challenges of the future, its R&D programs focus on 4 major areas: advanced manufacturing, embedded systems, data intelligence, control of radiation for health.
Two pillars structure the activity of 800 LIST employees :
Scientific excellence : LIST's state-of-the-art activities are the subject of publications in leading international conferences and journals, and are based on strong links with academic research ;
Openness to the academic and industrial world: In addition to its strong commitment to national industrial players, LIST is involved in more than 200 European collaborative projects and is associated with leading foreign academic laboratories.
LIST notably carries out large-scale work in the field of Advanced Manufacturing - the aim is to promote the deployment of innovative technologies within production units in order to improve the competitiveness of the industry.
For this, Artificial Intelligence (AI) is a flagship research sector: in this field, LIST's multidisciplinary know-how covers a wide spectrum of control or predictive maintenance applications. This mainly involves facilitating the operational deployment of AI technologies in the manufacturing context for which the implementation of supervised learning-based AI technologies very often stumbles on the lack of availability of qualified data or the cost of obtaining it (acquisitions and annotations). LIST is therefore carrying out innovative work on complementary approaches to overcome this lack of data. It may in particular be a matter of automatically creating qualified data or of implementing semi-supervised learning techniques, dispensing with manual annotation.
Your missions: Integrated into a multidisciplinary consortium (AI vision, NDT, Simulation), the candidate will be in charge of the development and implementation of innovative AI methodologies for manufacturing applications (defect control, etc.). This work will be done in close collaboration with the researchers and engineers of the teams involved in the project. For this, it will be:
§ Master the state of the art and ensure a technological watch on generative methods
§ Study the most appropriate algorithms to meet the application needs of the project
§ Improve methods and adapt them to the context of the project (s) in which you will be involved
§ Propose and develop tools dedicated to the constitution of learning bases adapted to the application contexts studied
§ Evaluate and validate the performance of the algorithms developed
§ Document the work and regularly communicate your results and progress to project managers and laboratory managers
Required profile : § Doctor or engineer in Artificial Intelligence
§ A significant experience in Deep Learning, ideally with generative networks (GAN, VAE ...)
§ A good command of Python programming tools and Deep Learning frameworks (TensorFlow, PyTorch).
§ Knowledge of C ++ language and image processing / computer vision would be appreciated, as well as experience in application development in an industrial context
The position to be filled already has internal funding for a minimum period of 24 months.
If you are autonomous and have a taste for challenge, if you appreciate teamwork and are motivated to advance research and technology, then do not hesitate to send an email to introduce yourself, along with your CV, to guillaume.gallou @ cea.fr .
Guillaume GALLOU - PhD Manufacturing & Agri / Agro Programs Manager
AI, Language and Vision Service Ambient Intelligence and Interactive Systems Department
Atomic Energy and Alternative Energies Commission List Institute | CEA Paris-Saclay Nano-INNOV | Build. 861-PC142
F-91191 Gif-sur-Yvette Cedex P.: +33 6 40 52 15 26 T. +33 1 69 08 83 37 S.: +33 1 69 08 40 86
[email protected] www-list.cea.fr
Contacts: Thierry HEDDE - CEA - Modeling Laboratory of Transfers in the Environment. Email : [email protected]
Pierre DURAND - Laboratory of Aerology (Univ. Toulouse III Paul Sabatier - CNRS).
Email : [email protected] (English version at the end)
MODELING OF VALLEY WINDS BY DESCENT ON A STATISTICAL SCALE
To model and monitor atmospheric emissions in an area with significant relief, it is is essential to represent the winds to the scale of this relief. For the CEA Cadarache site, by example, which is installed in a valley 5 km long and 1 km wide, local winds do not can be solved only with a high resolution weather forecast model (100 m in horizontal). However, obtaining simulation results with a high resolution model takes time.
calculations still incompatible with the constraints of operational weather forecasting (6 hours of calculation on our servers for 1 hour of forecast for Cadarache in 2020).
This is why the operational weather model of Cadarache only has a horizontal resolution of 1 km, which therefore does not allow it to resolve orographic effects of the valley.
In order to improve accuracy while maintaining acceptable calculation times, the Developing a statistical downscaling model seems to be an alternative solution to short term as long as its reliability can be demonstrated.
The object of the thesis is therefore to develop a downscaling model applied to a 3D mesh of the valley, with sufficient resolution to both model the aerology of the valley and follow a plume of pollution there using an atmospheric dispersion model.
A hundred meters in horizontal, of the order of ten meters in vertical and one step at least schedule in temporal resolution would seem to be parameters adapted to the needs of the CEA. Downscaling requires a robust and representative dataset of climatology and local aerology to allow learning of the method.
A campaign of measures carried out in 2017 for 4 months allowed us to collect data which nevertheless remains very spatially fragmented. To complete them it is proposed to use the WRF model in high resolution developed and validated in the laboratory.
It can be applied to the campaign observations with data assimilation forcing by these same observations; Thus will we be able to build a complete dataset on the valley with a resolution of 100 m over a period of 4 months.
It is then proposed, from simulations at operational resolution (1 km), to attempt to reproduce these high resolution wind fields by developing a descent model scale by choosing an artificial intelligence (AI) method using a neural network artificial (RNA) - already used successfully at one point in the valley. Other methods may also be evaluated.
During his thesis, the doctoral student will work within a small attentive and benevolent CEA team while remaining connected to university research via the Toulouse Aerology Laboratory.
He will be able to both become a specialist in applied research in the meteorological field and acquire digital and scientific skills that can be used in business.
MODELING OF VALLEY WINDS BY STATISTICAL DOWNSCALING In areas with complex and significant topography, forecasting the transport and dispersion of emissions requires to simulate the winds at a very local scale.
This is the case of the CEA Cadarache site located in a valley 5 km long and 1 km wide where local winds can only be resolved with a high- resolution (i.e. 100 m horizontally) weather forecast model.
However, such a high-resolution model requires computation times that are still incompatible with the constraints of operational weather forecasting (a computation time of 6 hours allows 1 hour of forecast only on Cadarache in 2020).
That is the reason why the operational meteorological model of Cadarache has a horizontal resolution as coarse as 1 km, which does not allow us to resolve the orographic effects of the valley.
The development of a statistical downscaling model seems to be an alternative solution in the near future provided that its reliability can be demonstrated.
The aim of the thesis is thus to develop such a downscaling model applied to a 3D meshing of the valley, with a resolution fine enough to both simulate the aerology of the valley and follow a pollution plume using an atmospheric dispersion model; about a hundred meters horizontally, ten meters vertically and less than one hour in time are the targeted resolutions.
Downscaling requires a robust dataset representative of local climatology and aerology for the learning phase of the method.
A measurement campaign carried out in 2017 during 4 months allowed us to collect wind measurements (as well as other variables) distributed both horizontally and vertically in the valley and which can be used as a learning data set. Nevertheless these observations remain scarce.
It is thus proposed to extend this data set with high resolution simulations, done with the WRF model already tuned and validated in the group.
Simulations could be done on the observation campaign period, taking benefit from these observations in the assimilation phase; it would thus be possible to constitute a complete data set on the valley with a resolution of 100 m over the entire 4-month period.
Afterwards, starting from the operational simulations with 1-km resolution, the aim will consist in reproducing the high resolution wind fields through the development of a downscaling model based on an artificial intelligence (AI) method using an artificial neural network (ANN) already used successfully at one specific location in the valley.
Other methods could also be tested during the thesis.
The PhD student will be involved in a small and sympathetic team on the CEA-Cadarache site. He / She will also be immersed in the academic world through the co-supervision at the Laboratory of Aerology (University of Toulouse).
The proposed work will allow to develop skills in applied meteorology, as well as in machine learning and computing science.
Hi all, Our team (IRT Railenium) is currently recruiting two post-doctoral fellows:
- A Postdoc topic : Autonomous Train environment reconstruction and surveillance based on pointcloud data (REF: VN2021-27)
- A Postdoctoral position in artificial intelligence (AI) for the recognition of multi-view instance and activity inside the autonomous train (REF: VN2021-28)
Candidates are invited to submit their applications on the recruitment tool:
REF : VN2021-27 : https://myshortlist.co/apply/railenium/1/6/apply
REF : VN2021-28 : https://myshortlist.co/apply/railenium/1/7/apply
Have a nice day !
Web site : RAILENIUM | Rail research & innovation
Cordialement,
Anaïs OUADOURI
Assistante ressources humaines / Human Resources Officer [email protected]
Absente le jeudi i-TRANS / RAILENIUM 180 rue Joseph-Louis Lagrange 59308 Valenciennes Cedex
Dear all, we have a postdoctoral position (3 years) for the European Project SONICOM (http://www.sonicom.eu).
The main goal of the successful candidate will be the development of methodologies capable to infer the personality traits of an individual (both self-assessed and attributed) from speech data rendered in VR and, possibly, from other nonverbal behavioural cues.
The preferred candidates have an established track record in speech/signal processing and machine learning (in particular deep networks).
Please apply by clicking on the following link: https://lnkd.in/dYVpY_KS
The deadline is on November 25th at 23.45.
Best, Alessandro
Hello everyone,
We are looking for a candidate to do a thesis in Rennes, at IRISA, in collaboration with LS2N, in Nantes.
Start date : January 2022 or as soon as possible in 2022
Subject : Combining educational resources through graph representation learning
Supervisors : Zoltan Miklos , Hoël Le Capitaine, Michael Foursov
Keywords : educational resources, knowledge graphs, graph representation learning, higher-order networks
Candidate profile : Master in computer science or equivalent (classified in the first third); good Python programming skills; machine learning, good bases on semantic web technologies (RDF, OWL, SPARQL); good oral and written communication skills in English.
Funding over 3 years (Labex Cominlabs) : Net salary ~ € 1,500.
To apply : send your application to [email protected] with a detailed curriculum vitae, your transcripts, a list of two references and your master's report in PDF format. Applications will be received until the position is filled.
Subject description : http://people.irisa.fr/Zoltan.Miklos/2021_PhD_position_at_IRISA.pdf
Thank you for disseminating this offer to your students.
Best regards, Zoltan
From CEA we are hiring!
Keywords: Data Stream, Machine Learning, Continuous Learning.
Description: The selected candidate will be part of “data streams” team of SID laboratory (CEA).
S/he will work within «Confiance.ai» project, a big French collective of unprecedented scope to design and industrialize systems based on trusted artificial intelligence, in which CEA participates.
Developed in SID premises, STREAMER is a cutting-edge data stream processing (Complex Event Processing) framework devoted to analyzing sequential data for electrical or industrial systems. In the scope of the project «Confiance.ai», the applicant will support the team in:
1- Studying trustworthy AI challenges that apply to real data stream processing. Such challenges may refer (but are not limited) to:
1.1 Continuous learning models applied to data streams in images.
1.2 Computation of confidence scores on the performance of the similarity measure for a model deployed in production.
1.3 Continuous adaptation of models to changing environments.
2. Developing algorithmic solutions to the aforementioned challenges.
3. Implementing and integrating such solutions within the STREAMER.
4. Collaborate with the project team and with researchers of the SID laboratory.
5 Participation in dissemination activities (as seminars, workshops, conferences, etc).Challenges described above will be decided on a rolling basis by the “scientific comity” of «Confiance.ai» project based on laboratories proposals. Their duration may be variable and adapted along the project.
Qualifications We look for a candidate with:
- Research engineer with experience in R&D and/or PhD.
- Background in machine learning.
- Strong programming skills (Java, Python).
- French and English proficiency speaking and writing.
- High motivation, self-learning and autonomy, teamwork skills
- Familiar with InfluxDB, Kafka or Redis [8] is a plus.
Where: CEA Saclay (DIGITEO Labs), France
Duration: 24 months.
Salary: From 2000 net euros/month depending on the applicant's experience.
Benefits: Free shuttles CEA from/to the laboratory to many points of Île de France. Partial refund of transport card.
Starting date: From 2022.
Contact Send your CV (better with a motivation letter) to Sandra Garcia Rodriguez ([email protected]) with email subject [CDD application].
Hello everyone, We are looking for a candidate to do a thesis in Rennes, at IRISA, in collaboration with LS2N, in Nantes.
Start date : January 2022 or as soon as possible in 2022
Subject : Combining educational resources through graph representation learning
Supervisors : Zoltan Miklos , Hoël Le Capitaine, Michael Foursov
Keywords : educational resources, knowledge graphs, graph representation learning, higher-order networks
Candidate profile : Master in computer science or equivalent (classified in the first third); good skills in Java programming, JavaScript, web applications, Python; good bases on semantic web technologies (RDF, OWL, SPARQL); good oral and written communication skills in English.
Funding over 3 years (Labex Cominlabs) : Net salary ~ € 1,500.
To apply : send your application to [email protected] with a detailed curriculum vitae, your transcripts, a list of two references and your master's report in PDF format. Applications will be received until the position is filled.
Subject description : http://people.irisa.fr/Zoltan.Miklos/2021_PhD_position_at_IRISA.pdf
Thank you for disseminating this offer to your students.
Best regards, Zoltan
Job title : Contractual teaching officer in computer science M / F at AgroParisTech
8-month fixed-term contract Position to be filled on 01/01/2022
The recruited person will be integrated for his teaching at the IT UFR of the MMIP department and for his research activities in the Ekinocs team of the UMR AgroParisTech / INRAe MIA-Paris .
For more details see the job description : https://place-emploi-public.gouv.fr/offre-emploi/chargee-d-enseignement-contractuelle-en-informatique-hf-reference-2021-747008/
Liliana IBANESCU
Director of the IT department of AgroParisTech Mathematical, Computer and Physics Modeling Department
AgroParisTech and UMR MIA Paris / INRAE
16, rue Claude Bernard 75005 Paris
Phone. (+33) 1 44 08 86 29 - Fax (+33) 1 44 08 16 66 E-mail: [email protected]
https://www6.inra.fr/mia-paris/Equipes/Membres/Liliana-Ibanescu
Hello, the national metrology and testing laboratory is currently looking for a post-doc (18-month contract) for a start-up in December 2021 / January 2022 in the field of analog AI evaluation.
The post-doc is part of a European project with Finnish and Polish partners for the design and validation of analog hardware capable of doing AI and will be used on a radar application in the medical field. .
I remain at the disposal of anyone who would like additional information
Regards
Rémi REGNIER PhD Research engineer in AI & robotics evaluation
(Research engineer in AI and robotics evaluation)
Testing Department
Phone. : 01 30 69 10 97
National metrology and testing laboratory 29 avenue Roger Hennequin 78197 Trappes Cedex - lne.fr
Project managers: Rémi Régnier ([email protected]), Olivier Galibert ([email protected])
Duration: 18 months
Entitled : Post-doctoral fellow in the evaluation of AI systems on analog hardware
You will join a team of ten engineers and doctors regularly accompanied by post- doctoral students, doctoral students and interns, specializing in the assessment and qualification of systems artificial intelligence.
This team is historically recognized for its expertise in the evaluation of automatic information processing systems (language processing, image processing, etc.).
In recent years, it has diversified in terms of areas application of its intelligence assessment expertise by dealing with subjects such as medical devices, collaborative industrial robots, autonomous vehicles, etc.
She capitalizes on the diverse and targeted know-how of its experts (NLP, imaging, robotics, etc.) in order to jointly find a satisfactory solution to the issue of evaluation and intelligent systems certification.
LNE is one of the three European partners of the AIR project of the Chist-Era program (2020- 2022, https://www.chistera.eu/projects/air) on the topic Analog Computing for Artificial Intelligence.
The project will focus on the use of radar technology for detection and tracking human vital signals (respiration, heart rate) for various applications such as monitoring of medical patients, intervention robots ...
In this context, LNE will have to put in place of new evaluation protocols for innovative analog-based AI systems and carry out a comprehensive evaluation campaign to promote this new product internationally type of hardware.
Herve Le Borgne [email protected]
In the context of the research project MultimEdia Entity Representation and Question Answering Tasks (ANR 2020-2024), a postdoctoral position is proposed for highly motivated candidates interested in multimedia understanding and natural language processing.
The main task of the post doc will consist in injecting some knowledge into a multimedia (image and text) entity representation to address Multimedia Question Answering. See the following link for details:
https://www.meerqat.fr/wp-content/uploads/2021/09/meerqat_postdoc_cea_lisn.pdf
The post-doc will be supervised by CEA and LISN. The candidate will be hired by CEA (Palaiseau, near Paris, France) for a 18-months post-doc. The LISN is located close to CEA on the Paris-Saclay University Campus.
*To apply **to the position*, send a CV (including publication list or a URL pointing to it, such as Google Scholar) and a cover letter to Hervé Le Borgne ([email protected]), Olivier Ferret ([email protected]), Sahar Ghannay ([email protected]) and Anne Vilnat ([email protected]).
You can write to [email protected] for any detail.
Thank you
Compliance Analyst (M / F) FircoSoft / LexisNexis Risk Solutions Paris
You want to use your linguistic skills and Automatic Language Processing and / or Translation, and participate to the growth of the world leader in filtering solutions banking transactions for financial institutions?
Join us as a Compliance Data Analyst (M / F)!
CDI position based in Paris 12th arrondissement.
Your responsibilities
Guarantor of international sanctions lists for our clients, you:
- Carry out an activity of monitoring and identification of news international sanctions lists
- Make updates and ensure delivery to our customers on time
- Provide support to customers if necessary
- Keep our internal documentation up to date
- Participate in continuous improvement projects related to your activity
- Maintain knowledge with regard to changes in anti-money laundering regulations (AML Compliance).
Your team
Within a multicultural team of Data Analysts, you work also in collaboration with sales representatives and consultants, our IT and Compliance services.
Your profile
- Coming from a Bac + 5 or equivalent training in Linguistics, you have a first experience in Automatic Language Processing
- Fluent English compulsory, mastery of a third language would be a more
- A mastery of Lotus Notes would be a plus
- Rigor, responsiveness and team spirit are assets that will help you will allow you to best achieve your goals
Our enterprise
Fircosoft is the recognized leader in mailing list filtering solutions. surveillance. More than 440 clients (representing more than 1,500 sites) rely on our software to filter their customer files and their financial transactions with watch lists.
We among them are nine of the ten most important institutions international financial institutions.
These institutions thus ensure that their operations comply with terrorist financing laws and embargoes, and put in place of optimal customer risk management.
Fircosoft is based in Paris and has offices in New York, London, Zurich, Chennai, Singapore, Tampa, Sao Paolo, and Pretoria.
With our global network of partners, we provide the services, support, as well as expertise to our customers in more than 85 countries.
Fircosoft is part of LexisNexis Risk Solutions.
You can send your CV by email to the following address: [email protected]