Machine Learning Staff Scientist at NSF-NCEMS

About the Position

Machine Learning Staff Scientist (Research Data Scientist – Intermediate or Advanced Professional) position dedicated to advancing the collaborative research of NCEMS and ICDS at Penn State.

Potential hybrid of remote and on‑site work with a minimum of 3 days per week on‑site at the Penn State University Park campus. Fully remote work is not permitted.

• Collaborate with NCEMS Working Groups to design, develop, and evaluate machine learning approaches for integrating, analyzing, and visualizing molecular and cellular biology data across the central dogma and regulatory processes.
• Prepare ML‑ready datasets by leading data wrangling, harmonization, standardization, quality control, and documentation to support robust training and reuse across biological modalities.
• Develop end‑to‑end ML workflows (feature/representation learning, training, validation, benchmarking, and uncertainty quantification) for multi‑omics and related data types.
• Build and optimize predictive and generative models (e.g., deep learning, probabilistic models, foundation‑model adaptation, graph/neural sequence models) to support synthesis research questions.
• Implement scalable training and inference pipelines using modern ML tooling (e.g., PyTorch/Tensor Flow/JAX), version control, containers, and HPC/GPU resources.
• Support the publication of intermediate data products, models, code, and documentation.
• Stay up‑to‑date with the latest advancements in machine learning, AI for biology, and the rapidly evolving landscape of public molecular and cellular datasets.

• M.S. or Ph.D. in Machine Learning, Computational Biology, Bioinformatics, Computer Science, Statistics, Data Science, or a related field is preferred.
• Strong proficiency in Python for scientific computing and machine learning, including experience with common ML libraries/frameworks (e.g., PyTorch, Tensor Flow, JAX, scikit‑learn).
• Demonstrated experience and understanding of core machine learning, deep learning and statistical methods such as regression and generalized linear models; classification and clustering; dimensionality reduction; sequence and time‑series modeling; deep learning architectures including CNNs, RNNs, GNNs, and transformers; generative modeling (e.g., diffusion and variational/auto‑regressive approaches), representation learning and self‑/weakly‑supervised learning, natural language processing, computer vision, and causal inference.
• Experience working with high‑dimensional, large‑scale molecular and cellular datasets (e.g., genomic, transcriptomic, epigenomic, proteomic, metabolomic/lipidomic, imaging‑derived, single‑cell, or multi‑omics data), including appropriate preprocessing and normalization strategies for ML.
• Solid understanding of molecular and cellular biology concepts sufficient to frame ML problems across the central dogma (sequence, expression, regulation, and protein function/structure) and to collaborate effectively with domain scientists.
• Experience with software engineering practices for research‑grade code, version control (Git), reproducible environments (containers/conda), HPC/GPU computing.
• Publications in peer‑reviewed journals demonstrating contributions to the field.
• Experience supporting/contributing to multi‑PI projects.

• If filled as Research Data Scientist – Intermediate Professional:
  Bachelor’s Degree and 1+ years of relevant experience; or an equivalent combination of education and experience accepted.
• If filled as Research Data Scientist – Advanced Professional:
  Bachelor’s Degree and 3+ years of relevant experience; or an equivalent combination of education and experience accepted.

The salary range for this position is $61,800.00 – $. Penn State provides a competitive benefits package for full‑time employees designed to support personal and professional well‑being, including medical, dental, vision coverage, retirement plans, paid time off, and a 75% tuition discount for employees, spouses, and children.

Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. If you are unable to use our online application process due to an impairment or disability, please contact 814‑865‑1473.