**Post-doc in Scientific Machine Learning**
- (2400006W)
- Commitment & contract: at least 2 Years_
- Location: IIT Erzelli, Genova_
**WHO WE ARE**:At IIT we work enthusiastically to develop human-centered Science and Technology to tackle some of the most pressing societal challenges of our times and transfer these technologies to the production system and society. Our Genoa headquarter is strictly inter-connected with our 11 centers around Italy and two outer-stations based in the US for a truly interdisciplinary experience.
For recent relevant publications from our lab, please see:
- V. Kostic, P. Novelli, A. Maurer, C. Ciliberto, L. Rosasco, M. Pontil. Learning dynamical systems via Koopman operator regression in reproducing kernel hilbert spaces. NeurIPS 2022.
- V. Kostic, P. Novelli, R. Grazzi, K. Lounici, M. Pontil. Learning invariant representations of time-homogeneous stochastic dynamical systems. ICLR 2024.
- V. Kostic, K. Lounici, H. Halconruy, T. Devergne, M. Pontil. Learning the infinitesimal generator of stochastic diffusion processes, Submitted 2024
- T. Devergne, V. Kostic, M. Parrinello, M. Pontil. From biassed to unbiased dynamics: an infinitesimal generator approach. Submitted, 2024.
- P Novelli, L Bonati, M Pontil, M Parrinello. Characterizing metastable states with the help of machine learning Journal of Chemical Theory and Computation 18 (9), 5195-5202, 2022.
- J Falk, L Bonati, P Novelli, M Parrinello, M Pontil. Transfer learning for atomistic simulations using GNNs and kernel mean embeddings. NeurIPS, 2023.
- R Grazzi, M Pontil, S Salzo. Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start. Journal of Machine Learning Research 24 (167), 1-37
Within the team your main responsibilities will be:
- to investigate open research problems in machine learning and computational physics,
- to write research papers and when appropriate, opensource software to fully reproduce the results presented in the papers,
- possibly, to be involved in coaching PhD students and interns.
**WHAT WOULD MAKE YOU SHINE**
- A PhD in Applied Mathematics, Physics, Engineering, Computer Science, or related disciplines;
- Good record of publications in top tier conferences/journals in ML and related disciplines;
- A strong background on a least one of the following areas:
- Machine Learning for dynamical systems and partial differential equations;
- Computational tools for numerical simulations, and a working knowledge of ML tools;
- Strong problem-solving attitude;
- Working knowledge of the ML ecosystem (Python, Pytorch, JAX, sklearn);
- The ability to properly report, organize and publish your research results;
- Good command of spoken and written English.
**COMPENSATION & BENEFITS**:
- Competitive salary package for international standards;
- Private health care coverage;
- Wide range of staff discounts;
**WHAT'S IN IT FOR YOU?**
- An equal, inclusive and multicultural environment ready to welcome you with open arms.
- We like contamination and encourage you to mingle and discover what others are up to in our labs!
- If paperwork is not your piece of cake, we got you! There's a specialized team working to help you with that, especially during your relocation!
- If you want your work to have a real impact, in IIT you will find an innovative and stimulating culture that drives our mission to contribute to the improvement and well-being of society!
- We stick to our values: integrity, courage, societal responsibility, and inclusivity. These guide our actions and drive us to achieve IIT's mission!
***
**Application's deadline**:31**st** October 2024***
**Primary Location** GENOVA ERZELLI
**Job** Postdoc
**Organization** Computational Statistics and Machine Learning
**Job Posting** Sep 24, 2024, 4:51:17 AM