Brookhaven National Laboratory · 1 day ago
Student Assistant - Workflow Development
Upton, NY
Full-time
Onsite
New GradBrookhaven National Laboratory is a multidisciplinary laboratory delivering discovery science and transformative technology. The Student Assistant will extend and maintain a Python-based workflow for compositional tuning and oxygen-vacancy formation in layered Li transition-metal oxides relevant to battery cathodes, supporting research and analysis for scientific outputs.
Information TechnologyLife ScienceSearch Engine
Responsibilities
You will extend and maintain a Python-based workflow to generate, modify, and submit DFT calculations for compositionally tuned layered oxide surfaces and vacancy structures
You will generalize the workflow to start from bulk structures (e.g., Materials Project entries), automatically construct surface slabs, and create targeted compositional variants and vacancy configurations
You will implement and refine post-processing steps to extract electronic-structure descriptors (e.g., vacancy energies, PDOS-derived quantities, band centers, bond metrics) into machine-learning–ready datasets
You will incorporate and compare machine-learning models (e.g., random forest and alternative regression methods), including model evaluation and feature-importance analysis (such as SHAP)
You will assist in data organization, documentation, and preparation of workflow tutorials and example notebooks for other CFN researchers
You will support scientific outputs (figures, tables, and analysis) for manuscripts on oxygen-vacancy formation and compositional tuning in layered Li oxides
Qualification
Required
Must be a college or graduate student in chemistry, materials science, physics, computer science, or a related STEM field
You have strong programming skills in Python and experience with scientific computing libraries (e.g., NumPy, pandas)
You are comfortable working in a Linux/Unix environment, including basic shell scripting and running jobs on remote systems or clusters
You communicate effectively, both verbally and in writing
You are committed to fostering an environment of safe scientific work practices
Preferred
You have experience with electronic-structure or atomistic simulation workflows (e.g., VASP, Quantum ESPRESSO) and associated Python tools such as ASE and pymatgen
You have prior experience with machine-learning tools in Python (e.g., scikit-learn) and familiarity with regression modeling and feature importance/interpretability methods (e.g., SHAP)
You have background knowledge in computational chemistry or materials physics, especially in modeling battery cathode materials, oxygen release, or defect/vacancy formation
You have experience with good software practices, including version control (Git/GitHub), code documentation, and basic testing
You have prior experience working with BNL facilities
You can work effectively in a collaborative team to tackle challenging problems, such as understanding complex scientific data
Benefits
Comprehensive employee benefits program
Company
Brookhaven National Laboratory
Brookhaven National Laboratory is a multi-purpose research institution focused on questions in basic and applied science.
Founded in 1947
1001-5000 employees
H1B Sponsorship
Brookhaven National Laboratory has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (123)
2024 (117)
2023 (104)
2022 (84)
2021 (98)
2020 (98)
Funding
Current Stage
Late StageTotal Funding
unknownKey Investors
US Department of Energy
2022-09-19Grant
Leadership Team
Thomas Schlagel
Advisor
Recent News
2025-12-24
2025-12-16
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