Job Summary

Postdoctoral Research Associate - Data-Driven Physics, ML/AI, and Advanced Detector R&D

The High Energy Physics Group at Purdue University invites applications for a Postdoctoral Research Associate to join an interdisciplinary research program at the intersection of data-intensive physics with nuclear/particle aspects, advanced detector R&D, machine learning and AI and emerging computational methods in quantum computing.

The position is intended for an excellent and broadly interested postdoctoral researcher with strong computational and data-analysis expertise who is interested in applied problems across experimental physics. The successful candidate contributes to applied nuclear and particle physics research leveraging machine learning and AI for data analysis and detector development, as well as exploratory work in quantum algorithms, depending on background and interests.

Core responsibilities and research directions include:

• Applied nuclear physics and spectroscopy, focusing on the analysis of data from photon spectrometer detectors recording nuclear collisions. A central component of this work is the development and application of machine-learning and AI techniques to identify weak, rare, or previously unknown nuclear transitions in complex spectral data.
• Advanced computational and data-science methods, including modern ML/AI workflows for pattern recognition, clustering, anomaly detection, and inference in large and noisy datasets. Exploratory work in quantum algorithms and quantum annealing for physics-driven optimization problems is also part of the research portfolio.
• Detector R&D for future facilities, leveraging Purdue’s infrastructure for detector development. The group operates a center of excellence for composite manufacturing and simulation for detector mechanics and cooling, as well as in-house facilities for the design, development, and construction of silicon detectors.

There is an optional opportunity to contribute a limited fraction of effort to research within the CMS experiment at CERN, particularly were expertise in ML/AI, data analysis, or detector-related topics can synergize with ongoing efforts. 

The postdoctoral researcher will work in a collaborative environment, mentor graduate and undergraduate students as appropriate, and contribute to publications and future research proposals.

Qualifications

Ph.D. in experimental particle physics, nuclear physics, astrophysics, engineering, computer science, or a closely related field (by start date)

Strong background in data analysis, computing, and scientific programming

Demonstrated ability to conduct independent research

Experience with machine learning / AI is highly desirable

Prior exposure to nuclear physics data, detector systems, or scientific instrumentation is an advantage but not required

Interest in interdisciplinary research spanning physics, computation, and advanced instrumentation

Appointment & Environment

Initial appointment for one year, renewable subject to performance and funding

Competitive salary and full benefits

Access to extensive computational, laboratory, and detector-development resources

A collaborative research environment with strong ties to national laboratories, international experiments, and interdisciplinary AI initiatives at Purdue

Application Process

The position is available starting immediately and applications will be considered until the position is filled. The appointment is initially for one year and renewable annually, subject to mutual satisfaction. The position will be based in West Lafayette, IN, although travel to other locations is expected for a number of short trips per year and/or extended periods of time.

Applications should include a curriculum vitae, a list of publications, a description of research interests (2 pages), and three letters of recommendation. Complete applications will be considered immediately. Please apply to link: https://careers.purdue.edu/job/Post-Doc-Research-Associate/35390-en_US/.

For information about the position, please contact Prof. Andreas Jung (anjung@purdue.edu ).