Postdoctoral Scholar (Machine Learning or Artificial Intelligence in Molecular and Cellular Biology)

A PhD in Computer Science, Data Science or a closely related field is required. The successful candidate will have a strong foundation in machine learning, artificial intelligence, statistical learning, scientific computing, data science, or related computational approaches. Candidates must have experience developing or implementing machine learning methods for large-scale data analysis, predictive modeling, or biological discovery. Expertise in Python is expected. A demonstrated ability to conduct research and produce scholarly outputs, as evidenced by publications in peer-reviewed journals. Familiarity with molecular and cellular biology concepts is also desirable. Candidates must be independent self-starters, have a strong work ethic, strong interpersonal and written communication skills, and the ability to work well in a collaborative team environment.

This position is full time, on-site at the Penn State University Park campus. This position does not permit remote work. This is a term appointment funded for one year from the date of hire, with an excellent chance for renewal based upon mutual agreement., Penn State provides a competitive benefits package for full-time employees designed to support both personal and professional well-being.

The National Synthesis Center for Emergence in the Molecular and Cellular Sciences (NCEMS) at Penn State University (ncems.psu.edu) seeks an outstanding scientist to fill a Postdoctoral Scholar position in Machine Learning or Artificial Intelligence housed within the Huck Institutes of Life Sciences at Penn State University.

NCEMS is an NSF-funded interdisciplinary research center positioned at the interface of data science, molecular and cellular biology, and quantitative physical sciences. The Center provides leadership in the integration of diverse, publicly available datasets to gain insights into emergent phenomena in molecular and cellular biology.

About the Position

The successful candidate, in collaboration with faculty and research staff at NCEMS, will conduct original research applying machine learning, artificial intelligence, computer science, statistical learning, or related computational approaches to problems in molecular and cellular biology. Research may involve large-scale public datasets, biological data harmonization, representation learning, predictive modeling, foundation models, network analysis, graph-based learning, uncertainty quantification, scientific machine learning, or interpretable AI.