Research - Laboratory/Non-Laboratory, Staff/Administrative
The experimental high energy physics (HEP) group at the University of Minnesota (UMN) invites applications from outstanding candidates for the position of postdoctoral researcher or research scientist to work on the CMS experiment and to develop and apply findable, accessible, interoperable, and reusable (FAIR) principles to artificial intelligence (AI) models and data in high energy physics. Transformational progress in AI has been driven by the ubiquity of large datasets such as ImageNet. Within HEP, creating and publishing open, realistic, and FAIR datasets can shed light on the unique challenges in this domain and usher in new groundbreaking and physics-inspired ideas in AI.
FAIR4HEP is a joint DOE-funded venture between UIUC, MIT, UMN, and UCSD. The goal of the multi-institution and interdisciplinary project is to curate data sources from HEP, develop software frameworks to automatically train, evaluate, and compare benchmark AI models for charged particle tracking, Higgs boson identification, detector calibration, event reconstruction, and more, and publish sharable AI models and data following FAIR principles. The successful candidate is expected to take a leading role in these efforts as well as in the CMS experiment. The postdoctoral researcher will be affiliated with UMN and mentored by Prof. Rusack, but is encouraged to collaborate with all partner institutions.
The CMS group at the University of Minnesota (Strobbe, Mans, Rusack) has leading roles in a variety of physics analyses, ranging from searches for new particles to precision measurements of the Higgs boson, as well as heavy involvement in the CMS endcap calorimeter upgrade project for the High-Luminosity LHC.
Primary duties: 75%: Research, divided approximately equally between data analysis and detector upgrades 10%: Supervision of graduate students and/or undergraduates participating in relevant research 15%: Communicating research to the broader community by writing papers, submitting them for publication in peer-reviewed journals. Giving presentations at universities, presenting results at domestic and international conferences, and participating in workshops.
Other duties of a similar scope as assigned.
Qualifications Required Qualifications: A PhD in physics, statistics, computer science, machine learning, data science, or related fields is required. Prior experience in software development and machine learning is advantageous, but not essential. Substantial research and publication record.
Preferred Qualifications: Preference will be given to candidates with prior experience in software development and machine learning is advantageous, but not essential.
Internal Number: 338242
About University of Minnesota, Twin Cities
The University of Minnesota, founded in the belief that all people are enriched by understanding, is dedicated to the advancement of learning and the search for truth; to the sharing of this knowledge through education for a diverse community; and to the application of this knowledge to benefit the people of the state, the nation, and the world.