Post-doc in Machine Learning and Computational Chemistry
Pubblicato il 20-10-2026 - Istituto Italiano Di Tecnologia in Genova
Post-doc in Machine Learning and Computational Chemistry Italy
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Commitment & contract: collaboration contract
Step into a world of endless possibilities, together let's leave something for the future!
At IIT, we are committed to advancing human-centered Science and Technology to address the most urgent societal challenges of our era. We foster excellence in both fundamental and applied research, spanning fields such as neuroscience and cognition, humanoid technologies and robotics, artificial intelligence, nanotechnology, and material sciences, offering a truly interdisciplinary scientific experience. Our approach integrates cutting-edge tools and technology, empowering researchers to push the limits of knowledge and innovation.
With us, your curiosity will know no bounds.
We are dedicated to providing equal employment opportunities and fostering diversity in all its forms, creating an inclusive environment. We value the unique experiences, knowledge, backgrounds, cultures, and perspectives of our people. By embracing diversity, we believe science can achieve its fullest potential.
THE ROLE 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 postdoctoral researcher 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,
that is to say 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. Such algorithms will be of strategical importance in help addressing some of mankind's cogent problems like for instance the transition to a green economy.
Good candidates are either people with expertise in machine learning methodologies who are interested into applying them to computational chemistry, as well as computational physicists or chemists that have already a working knowledge of machine learning tools.
Within the research team, your main responsibilities will be:
investigate open research problems in machine learning and computational physics and chemistry,
write research papers and when appropriate opensource software for reproducibility and dissemination possibly be involved in coaching PhD students and interns.
ESSENTIAL REQUIREMENTS A PhD in Physics, Chemistry, Computer Science, Applied Mathematics, or related disciplines;
Good record of publications in top tier conferences/journals in ML and/or Comp. Chemistry;
Strong problem-solving attitude;
Strong Programming skills (Python, TensorFlow, etc.)
The ability to properly report, organize and publish your research results;
Good command of spoken and written English. xysqume
COMPENSATION PACKAGE A yearly gross salary ranging between 35.000,00 and 42.000,00 euro
Private health care coverage depending on your role and contract
Candidates from abroad or Italian citizens who have carried scientific research activity permanently abroad and meet specific requirements, may be entitled to a deduction from taxable income of up to 90% from 6 to 13 years.
Application's deadline: November 30, 2026.
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