Post-doc position in Machine Learning and Computational Chemistry at Istituto Italiano di Tecnologia in Genoa
Numerical simulations of physical systems coupled with machine learning techniques have the potential to revolutionize the way in which science is conducted.
Meeting this challenge requires a multi-disciplinary approach in which experts from physics and machine learning work together. To this end, we are seeking a talented and motivated Postdoc to join a collaborative project between the Atomistic Simulations and Computational Statistics and Machine Learning Research Units at IIT, led by Profs. Michele Parrinello and Massimiliano Pontil, respectively. The goal of the project is to combine the expertise of the two units on advanced numerical simulations and machine learning theory and algorithms. The successful candidate will be engaged in designing novel physics-informed learning algorithms for atomistic simulations, which are more efficient, interpretable, and reliable than currently available methods.
Good candidates are either people with expertise and a proven record in machine learning who are interested in applying them to computational chemistry, as well as computational physicists or chemists that have already a working knowledge of machine learning tools.
Please apply here: https://iit.taleo.net/careersection/ex/jobdetail.ftl?lang=en&job=220000A4
Deadline: February 15, 2023
