Find Jobs
Find Jobs Near You – Available Work in Your Location
Skip to job details
LU
Lehigh University
Postdoctoral Research Associate in Control Systems, Artificial Intelligence, and Scientific Machine Learning for Fusion Energy
Career Insights for Data Scientist
See where this job fits in the broader career landscape. Knowing your career path helps you see what's possible from here.
Scorecard
Based on Pennsylvania data
Review key factors to help you decide if this role fits your goals. How is this calculated?
What they do
A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.
$105,420 / year median in Pennsylvania
+18% projected growth
Job Description
The Lehigh University Plasma Control Laboratory invites applications for a Postdoctoral Research Associate position focusing on control systems engineering, artificial intelligence (AI), and scientific machine learning (SciML) applied to nuclear fusion energy. The successful candidate will join the Lehigh University Plasma Control Group (LU-PCG) and contribute to advanced control synthesis, neural observer development, scenario optimization, and AI-enabled digital twins for magnetically confined fusion plasmas in tokamaks. This position targets experts in control theory, data science, or machine learning who are seeking to apply their expertise to nuclear fusion, as well as researchers with established backgrounds in plasma control. A key feature of this position is the opportunity to collaborate with major U.S. and international fusion facilities (such as DIII-D, NSTX-U, KSTAR, WEST, and ITER) and contribute to LU-PCG's research under the U.S. Department of Energy's (DOE) GENESIS Mission. Research will involve developing fast neural surrogate models, state estimators/virtual sensors, multi-input multi-output (MIMO) closed-loop controllers (MPC, RL, hybrid RL-MPC), and real-time actuator management architectures embedded in MATLAB/Simulink digital-twin environments (COTSIM). This role offers a unique opportunity to work with Professors Eugenio Schuster and Tariq Rafiq in the field of advanced fusion control systems, engage in cutting-edge control/AI research, build a larger and stronger professional network, and gain experience in mentorship and academic service.