Postdoc Position in Precision Machine Learning for Particle Phenomenology

INFN; Genova; In loco; EUR 30.000 - 45.000; Tempo pieno

Descrizione del lavoro

A research institution in Italy is seeking applications for a postdoctoral position focusing on precision machine learning for particle phenomenology. The role involves developing ML-based tools and models, suitable for candidates with a PhD in physics or a related field and an interest in machine learning techniques. This is a full-time role starting in Fall 2026, ideally for Italian citizens with international experience.

Competenze

• Background in theoretical or phenomenological particle physics.
• Interest in machine learning techniques.
• Experience with simulation and modelling tools.

Mansioni

• Develop and validate ML-based tools for simulation.
• Work on generative models for collider physics.
• Conduct likelihood-free inference and global EFT fits.

Conoscenze

Machine Learning

Particle Physics

Data Analysis

Formazione

PhD in Physics or related field

Descrizione del lavoro

Postdoc Position in Precision Machine Learning for Particle Phenomenology

The INFN Genova high‑energy phenomenology group is seeking applications for a two‑year postdoctoral position in particle physics, with a focus on precision machine learning and its applications to particle phenomenology.

The group (Biggio, Frixione, Marzani, Ridolfi, Torre) has broad interests in collider physics, effective field theories, higher‑order calculations, parton distribution functions, and new physics searches, both within and beyond the Standard Model. It maintains close interactions with local experimental groups involved in ATLAS, CMS, LHCb and astroparticle physics, and has several ongoing projects with international collaborators.

The successful candidate is expected to contribute to the activities of the INFN initiative PML4HEP – Precision Machine Learning for High‑Energy Physics, coordinated from Genova. Research topics may include:

• development and validation of ML‑based tools for simulation, inference, or modelling;
• generative models for collider physics;
• likelihood‑free inference;
• global EFT fits;
• uncertainty quantification in ML.

Candidates with a background in theoretical or phenomenological particle physics, and an interest in machine learning techniques, are encouraged to apply.

Open to:

• Italian citizens who, at the time of the application, hold a position in a foreign institution and have been continuously abroad for at least three years.

Application details:

• Position start: Fall 2026, funded by INFN.
• Submit electronically through the INFN portal: https://reclutamento.dsi.infn.it/en
• Detail of the call: https://jobs.dsi.infn.it/dettagli_job.php?id=4422
• Full PDF of the call: https://jobs.dsi.infn.it/borseassegni/pdf/getfile.php?filename=28201.pdf

For informal inquiries, please contact: Riccardo Torre ([e-mail])

Job details

• Seniority level: Internship
• Employment type: Full‑time
• Job function: Research, Analyst, and Information Technology
• Industry: Research Services

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