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Physics Informed Machine Learning Jobs in West Lafayette, IN

Recovery Associate

Lafayette, IN · On-site

$13.25 - $16.20/hr

Use general office equipment such as telephone, copy machine, fax machine, calculator, computer ... Actively participate in learning initiatives offered such as training programs, workshops, and ...

Recovery Associate

Lafayette, IN · On-site

$13.25 - $16.20/hr

Use general office equipment such as telephone, copy machine, fax machine, calculator, computer ... Actively participate in learning initiatives offered such as training programs, workshops, and ...

Recovery Associate

Lafayette, IN · On-site

$13.25 - $16.20/hr

Use general office equipment such as telephone, copy machine, fax machine, calculator, computer ... Actively participate in learning initiatives offered such as training programs, workshops, and ...

Physics Informed Machine Learning information

See West Lafayette, IN salary details

$5

$19

$24

How much do physics informed machine learning jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for physics informed machine learning in West Lafayette, IN is $19.30, according to ZipRecruiter salary data. Most workers in this role earn between $12.02 and $24.52 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the physics informed machine learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in physics informed machine learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What is a physics informed machine learning?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are popular job titles related to Physics Informed Machine Learning jobs in West Lafayette, IN? For Physics Informed Machine Learning jobs in West Lafayette, IN, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in West Lafayette, IN look for? The top searched job categories for Physics Informed Machine Learning jobs in West Lafayette, IN are:
What cities near West Lafayette, IN are hiring for Physics Informed Machine Learning jobs? Cities near West Lafayette, IN with the most Physics Informed Machine Learning job openings:
Infographic showing various Physics Informed Machine Learning job openings in West Lafayette, IN as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $40,151 per year, or $19.3 per hour.

Post Doc Research Associate

Purdue University

West Lafayette, IN • On-site

Full-time

Re-posted 10 hours ago


Purdue University rating

7.5

Company rating: 7.5 out of 10

Based on 136 frontline employees who took The Breakroom Quiz

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Job description

Post Doc Research Associate
City: West Lafayette
Job Description:
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 ).

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