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.
YOUR TEAM: The position is within the Computational Statistics and Machine Learning (CSML) research unit at IIT. The successful candidate will be engaged in designing novel learning algorithms for numerical simulations of physical systems, with a focus on machine learning for dynamical systems. CSML has a strong focus on ML theory and algorithms, but also significant multidisciplinary interactions with other IIT groups in areas ranging from Atomistic Simulations, to Neuroscience and Robotics. We have also recently started international collaboration on Climate Modelling.
The group hosts applied mathematicians, computer scientists, physicists and computer engineers, working together on both theory, algorithms and applications. Machine learning techniques, coupled with numerical simulations of physical systems have the potential to revolutionize the way in which science is conducted. Meeting this challenge requires a multi-disciplinary approach in which experts from different disciplines work together.
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, open source 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 at 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;Numerical optimization and its application to machine learning and deep learning;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! Please submit your application using the online form and CV, a short research statement (max 2 pages) and names of two referees. Application's deadline: 31st October 2024 We inform you that the information you provide will be used solely for the purposes of evaluating and selecting professional profiles in order to meet the requirements of Istituto Italiano di Tecnologia. Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security. Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone Tel: +39 010 28961 - email: dpo[@]iit.it ).
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