Post Doctoral Research Associate

Title:
Post Doctoral Research Associate

Department:
MT School of Management

Reports To:
Professor MT School of Management

Position Type:
Staff

Position Summary:
The
sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC) at Brookhaven
National Laboratory is seeking a highly motivated post-doctoral researcher to
join an innovative project at the intersection of high-energy physics, data
science, and real-time data processing. The goal of the sPHENIX experiment is
to advance the understanding of Quantum Chromodynamics (QCD) by studying the
dynamics of heavy quarks, jet substructure, and parton energy loss in
high-energy collisions.

The
post-doctoral researcher will contribute to developing a novel Large
Language Model (LLM) based approach for event data analysis in the sPHENIX
data acquisition system. The sPHENIX experiment employs cutting-edge tracking
technology, including the Monolithic-Active-Pixel-Sensor (MAPS)-based VerTeX
detector (MVTX) and the INTT detector, to perform high-precision
vertexing and momentum measurements crucial for identifying heavy-flavor
events. However, due to the inherently low probability of heavy quark
production in proton-proton collisions, efficient data acquisition and real-time
trigger detection are critical for identifying key events, such as those
involving bottom quarks (bb).

The
post-doctoral candidate will lead the development of a LLM-based model to identify trigger event. This innovative approach leverages the power
of machine learning to enhance data filtering and optimize event selection,
facilitating the study of rare, high-energy phenomena.

Essential Functions:
- Develop and implement
LLM-based models for event analysis and trigger detection in the sPHENIX
experiment.
- Collaborate with physicists,
data scientists to optimize the data analysis pipeline for efficient event
selection, with a focus on quark production.
- Analyze data from high-energy
proton-proton and heavy-ion collisions, focusing on heavy quark dynamics,
jet substructure, and QCD phenomena.
- Present results in internal
meetings, workshops, and international conferences.
- Contribute to publications and
reports related to the project's findings.

Prerequisite Qualifications:
- Ph.D. in Data Science, Computer
Science or a related field, with a strong focus on machine learning,
artificial intelligence.
- Strong programming skills in
Python.
- Experience with Large Language
Models (LLMs), deep learning frameworks.
- Excellent problem-solving
abilities and a strong interest in interdisciplinary research.
- At the university's
discretion, the education and experience prerequisites may be exempted
where the candidate can demonstrate to the satisfaction of the university,
an equivalent combination of education and experience specifically
preparing the candidate for success in the position.

Preferred Qualifications:
Strong programming skills in
C, C++, or similar languages.

Bargaining Unit:
AFT-UCAN

FLSA:
Exempt
Full-Time

Special Instructions to
Applicants:
Interested
candidates should submit the following:
- A cover letter outlining your
qualifications and research interests.
- A detailed curriculum vitae
(CV).
- Contact information for at
least three academic references (optional).

The
position will be based at New Jersey Institute of Technology, with potential travel
to Brookhaven National Laboratory as needed.