Research engineer active on-line training for deep surrogates h/f

A propos d'Inria

Inria est l'institut national de recherche dédié aux sciences et technologies du numérique. Il emploie 2600 personnes. Ses 215 équipes-projets agiles, en général communes avec des partenaires académiques, impliquent plus de 3900 scientifiques pour relever les défis du numérique, souvent à l'interface d'autres disciplines. L'institut fait appel à de nombreux talents dans plus d'une quarantaine de métiers différents. 900 personnels d'appui à la recherche et à l'innovation contribuent à faire émerger et grandir des projets scientifiques ou entrepreneuriaux qui impactent le monde. Inria travaille avec de nombreuses entreprises et a accompagné la création de plus de 200 start-up. L'institut s'eorce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie. Research Engineer: Active On-line Training for Deep Surrogates
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : CDD

Contrat renouvelable : Oui

Niveau de diplôme exigé : Bac +5 ou équivalent

Fonction : Ingénieur scientifique contractuel

Niveau d'expérience souhaité : Jeune diplômé

A propos du centre ou de la direction fonctionnelle

The Centre Inria de l'Université de Grenoble groups together almost 600 people in 26 research teams and 9 research support departments.

Staff is present on three campuses in Grenoble, in close collaboration with other research and higher education institutions (Université Grenoble Alpes, CNRS, CEA, INRAE, ), but also with key economic players in the area.

The Centre Inria de l'Université Grenoble Alpes is active in the fields of high-performance computing, verification and embedded systems, modeling of the environment at multiple levels, and data science and artificial intelligence. The center is a top-level scientific institute with an extensive network of international collaborations in Europe and the rest of the world.

Contexte et atouts du poste

The candidate will join the INRIA team located on the campus of the Univ. Grenoble Alpes near Grenoble. The DataMove team is a friendly and stimulating group with a strong international visibility, gathering Professors, Researchers, PhD and Master students all pursuing research on High Performance Computing.

This work experience will bring you skills from high performance computing up to deep learning that are in high demand.

The city of Grenoble is surrounded by the Alps mountains, offering a high quality of life, and where you can experience all kinds of mountain related outdoors activities and more.

Principales activités

Our team develops Melissa (), a framework running on supercomputers for managing an ensemble of simulations (several executions of the same simulation code) with on-line processing of the data produced by these simulations. Melissa has been the support of innovative research works with latests developments focusing on the training of deep surrogates, i.e. training a neural network to approximate the simulation code producing the training data. On-line training enables to steer the data generation by choosing the parametrization of the next simulations instances to run. We have been developing a series of steering approaches, often called active learning, based on Population Monte Carlos Importance Sampling () and more recently on diffusion networks. So far this work as lead to a proof of concept, but results need to be consolidated, published and integrated in the production version of Melissa.
The goal of this research engineer position is to:- Consolidate the methodology based on diffusion networks, modify Melissa accordingly when needed;
- Develop extensive benchmarks based on different PDEs (mainly from the APE Benchmark suite);
- Conduct experiments at scale on supercomputers to compare base approaches (no active learning) with different state-of-the-art active learning algorithms including our solutions;
- Participate to the redaction of a publication exposing the methodologies and experimental results, including reproducibility artefacts;
- Consolidate the code to integrate active learning in the main branch of Melissa so it can be distributed to potential users;
- Participate to the Melissa community (blog writing, training, bug fixing, documentation effort, advising of interns,).

Compétences

We welcome candidates with a master (or equivalent title) in computer science, experience with parallel programming, distributed data processing, deep learning or numerical solvers.

Expected technical skills include Linux, Python and some C/C++ programming practice, mastering of development processes is a plus (git, continuous integration, containers, etc.).

A reasonable level of English is required.

To apply submit you CV, references, recent marks, and if available your last Intership/Master Thesis manuscript. With your application provide any element (github account, code snippets, etc.) that could help us assess you skills beyond your academic record, as well as a few references of persons we can contact to get some feedback on your qualities.

Avantages

- Subsidizedmeals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking (90 days / year) and flexible organization of working hours
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage under conditions

Rémunération

From 2,692 € (depending on experience and qualifications).