-
models for composites of arbitrary structures to predict their homogenized properties. The candidate will also work closely with AI experts to develop workflows for composite structure discovery given
-
) of electrochemical energy storage devices (diagnosis) and predict the SOH into the future (prognosis). The primary projects this postdoc will contribute to relate to lithium-ion batteries, advanced lead-acid batteries
-
research will involve synergetic collaborations with a multi-disciplinary team involving engine modelers, CFD experts, and computational scientists to enhance the predictive capability for next-generation
-
candidate will work on cutting-edge research integrating genome-scale language models (GenSLMs) with deep mutational scanning data, and experimental virology to predict viral evolution and identify emerging
-
, scikit-learn, TensorFlow, PyTorch). Hands-on experience with data science workflows, including ML/AI model development, training, and evaluation for predictive analytics or decision support. Excellent oral