Location: University of Massachusetts Lowell Lowell, Massachusetts
Topics: Machine learning, computational materials, energy storage, nuclear

Dates: Spring 2023, Fall 2023

We are seeking new PhD candidates for our research group that can work in multiple areas including: 1) machine learning-assisted spectroscopy for studying ionic liquid structure, 2) predicting thermal-electrical properties in doped ceramics for grid-scale thermal energy storage, 3) developing machine-learning based interatomic potentials for modeling molten salts, 4) generative ML modeling organic ligands for nuclear waste separation, and other energy applications.

Relevant Skills

• Background in materials physics / physical chemistry / nanoscience / chemical engineering / nuclear engineering / engineering
• Experience of atomic-scale modeling of electronic properties: DFT, hybrid DFT, GW, DOS, etc.
• Experience in machine learning (neural networks, autoencoders, GANs, etc.)
• Experience in programming is required (python preferred)
• Fluency in written and spoken English

Candidates should send a CV, transcript and statement of interest to [email protected]. Target start date would be Spring 2023 or Fall 2023. For more information about our group: https://sites.uml.edu/stephen-lam/research/