Huck Institutes of the Life Sciences NSF NCEMS Postdoctoral Scholar

Penn State University•University Park, IL

11d•Onsite

About The Position

The National Synthesis Center for Emergence in the Molecular and Cellular Sciences (NCEMS) at Penn State University seeks an outstanding scientist to fill a Postdoctoral Scholar position in Machine Learning or Artificial Intelligence. 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. The successful candidate 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. 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.

Requirements

A PhD in Computer Science, Data Science or a closely related field is required.
A strong foundation in machine learning, artificial intelligence, statistical learning, scientific computing, data science, or related computational approaches.
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.
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.

Nice To Haves

Familiarity with molecular and cellular biology concepts is also desirable.

Responsibilities

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.
Produce scholarly outputs, as evidenced by publications in peer-reviewed journals.