Postdoctoral Researcher in Neutrino Physics - DUNE (M/F)

EURAXESS Ireland; Grenoble; Hybrid; EUR 42,000 - 54,000; Full time

Job summary

The Laboratoire de Physique Subatomique et de Cosmologie (LPSC) in Grenoble invites applications for a First Stage Researcher postdoc to work on the DUNE experiment. The successful candidate will analyze ProtoDUNE-VD data (beam and cosmics) and help prepare the fitting framework for the first data.

Responsibilities include developing event reconstruction tools and high-performance computing components, contributing to sensitivity studies, and possibly helping with assembly/tests of readout

Qualifications

• PhD in particle physics or closely related field.
• Experience with data analysis and associated statistical methods.
• Strong programming skills (C++, Python, ROOT).
• English proficiency (written and spoken) is required.

Responsibilities

• Analyze ProtoDUNE-VD prototype's first data (beam and cosmics).
• Characterize ProtoDUNE-VD and estimate its performance.
• Development of event reconstruction tools.
• Developments for a High-Performance Computing fitting framework.
• Major contributions to sensitivity studies for DUNE's main analysis.
• Possible contributions to the assembly and tests of the charge readout planes at LPSC and to the construction of the far detector at SURF.

Skills

Data analysis

C++ programming

Python programming

English proficiency

Education

PhD in particle physics

Tools

ROOT

Deep learning

HPC

Job description

Organisation/Company CNRS Department Laboratoire de physique subatomique et de cosmologie Research Field Physics Researcher Profile First Stage Researcher (R1) Application Deadline 30 Oct 2026 - 23:59 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Dec 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The DUNE experiment will study beam neutrino oscillations to determine the neutrino mass ordering, measure the CP-violating phase, and perform high-precision measurements of the neutrino oscillation parameters to probe the existence of physics beyond the Standard Model.

The 17-kton Liquid Argon Time Projection Chambers are currently under construction at SURF. Large-scale prototypes are being tested at CERN. The postdoctoral researcher will analyze ProtoDUNE-VD's recent data (beam and cosmics) to characterize the detector and estimate its performance. At the same time, the reconstruction and analysis tools that will be used in DUNE's final measurements are being developed and continue to be improved. The postdoctoral researcher will join the ongoing effort dedicated to updating DUNE's sensitivity and to preparing the fitting framework for the first data.

• Analysis of the ProtoDUNE-VD prototype's first data (beam and cosmics).
• Characterization of ProtoDUNE-VD and estimation of its performance.
• Development of event reconstruction tools.
• Developments for a High-Performance Computing fitting framework.
• Major contributions to sensitivity studies for DUNE's main analysis, the long baseline oscillation analysis (determination of the neutrino mass ordering, CP-violation, etc.).
• Possible contributions to the assembly and tests of the charge readout planes at LPSC and to the construction of the far detector at SURF.

The Laboratoire de Physique Subatomique et de Cosmologie de Grenoble (LPSC, http://lpsc.in2p3.fr ) is a mixed research unit, combining CNRS-IN2P3, the Université Grenoble Alpes (UGA) and the Grenoble INP engineering and management schools network, and gathering around 230 personnel.

The LPSC DUNE team is currently composed of 5 permanent researchers and one PhD student. LPSC is responsible for the production of half of the CRP for the Far Detector Vertical Drift module. The team is also heavily involved in the long-baseline oscillation analysis and the ProtoDUNE analysis.

• PhD degree in particle physics or closely related field.
• Experience with data analysis and associated statistical methods.
• Strong programming skills (C++, Python, ROOT, etc.)
• English proficiency (written and spoken) is required.
• Experience with deep-learning techniques and libraries welcome.
• Past experience in neutrino oscillation and/or LAr TPC experiment welcome.