Publisher
source

Wouter Verkerke

4 months ago

Postdoc position in the ATLAS group: Global Optimization of diHiggs Measurements National Institute for Subatomic Physics (NIKHEF) in Netherlands

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Deadline

Expired

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Country

Netherlands

University

National Institute for Subatomic Physics (NIKHEF)

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Keywords

Computer Science
Experimental Physics
Statistical Analysis
Artificial Intelligence
Particle Physics
Computational Physics
Flavour
Electroweak Theory
Optimisation
Physics
Machine learning

About this position

Nikhef, the National Institute for Subatomic Physics in the Netherlands, is a leading research center in particle and astroparticle physics, collaborating with major Dutch universities and international experiments such as ATLAS at CERN. The Nikhef ATLAS group is deeply involved in detector construction, data acquisition, and advanced physics data analysis, with a strong focus on Higgs boson physics and searches for new physics. This postdoctoral position centers on the global optimization of diHiggs measurements, a key challenge for the LHC following the discovery of the Higgs boson. The successful candidate will develop and apply machine-learned surrogate models to optimize selection criteria for all two-Higgs decay signatures, aiming to surpass traditional local optimization methods. The project also explores future AI models capable of direct data analysis from low-level data. The postdoc will be embedded in the Nikhef diHiggs group, collaborating with PhD students and staff on Run-3 analyses of various Higgs decay channels. The position is part of a NWO-funded program, "The potential of the Higgs boson," which includes multiple PhD and postdoc positions focused on Higgs boson potential studies. The role offers excellent employment conditions, including a three-year contract, competitive salary, and additional benefits. Applicants should have a PhD in high-energy physics, strong data analysis and software skills, and experience with machine learning in particle physics. The application deadline is November 16, 2025, with interviews scheduled for December 8-10. For more details, candidates can refer to the Nikhef employment page or contact the listed supervisors.

Funding details

Available

What's required

Applicants must have an (almost) completed PhD degree in high-energy physics. The ideal candidate will have a strong track record in data analysis, good software skills, several years of research experience in experimental particle physics, and significant experience with machine learning algorithms applied to data selection in particle physics. A knowledge security check may be part of the selection procedure.

How to apply

Apply online via the provided application link by November 16, 2025. Prepare a short cover letter, CV, and contact details for at least three referees. Indicate the position of interest in your cover letter. Interviews are expected December 8-10.

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