Join the Computational Statistics and Machine Learning Research Unit at IIT as a Postdoc
Join the Computational Statistics and Machine Learning Research Unit at IIT as a Postdoc. Design novel learning algorithms for numerical simulations of physical systems, with a focus on machine learning for dynamical systems. Apply by November 10, 2024.
The Italian Institute of Technology (IIT) is seeking a talented and motivated Postdoc to join the Computational Statistics and Machine Learning Research Unit, led by Prof. Massimiliano Pontil. The successful candidate will design novel learning algorithms for numerical simulations of physical systems, with a focus on machine learning for dynamical systems. CSML’s core focus is on ML theory and algorithms, while significant multidisciplinary interactions with other IIT groups apply our research outputs 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 theory, algorithms and applications. ML 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. Candidates with a strong background in at least one of the following areas will be given priority in hiring: 1) ML for dynamical systems and partial differential equations; 2) Computational tools for numerical simulations, and a working knowledge of ML tools; 3) Numerical optimization and its application to machine learning and deep learning.
To apply, please submit your application using the online form, CV, a short research statement (max 2 pages) and names of two referees. The deadline for applications is November 10, 2024.
Tags: Postdoc, Italian Institute of Technology, IIT, Computational Statistics and Machine Learning Research Unit, ML, Dynamical Systems, Numerical Simulations, Physical Systems, Machine Learning, Deep Learning, Applied Mathematics, Computer Science, Physics, Computer Engineering