KC Santosh
5 days ago
Biomedical AI Scientist Positions in Artificial Intelligence, Machine Learning, and Biomedical Informatics (PhD, Postdoc, Masters) University of South Dakota in United States
I am hiring Biomedical AI Scientists for grant-funded research positions at the University of South Dakota.
South Dakota State University
United States
Date not provided
Keywords
Description
The University of South Dakota (USD) Artificial Intelligence (AI) Research group, housed in the Department of Computer Science, is recruiting multiple Biomedical AI Scientists for full-time, grant-funded research positions. These roles are part of the South Dakota Biomedical Computation Collaborative (SDBCC), a federally funded initiative focused on advancing foundational machine learning models for large-scale biomedical and clinical datasets, including genomics, transcriptomics, proteomics, medical imaging, and electronic health records. The research aligns with USD’s mission to lead in AI and machine learning innovation, supporting South Dakota’s flagship university and its top programs in AI.
Successful candidates will join a vibrant, multidisciplinary team of computing scientists, biomedical researchers, clinicians, and engineers, collaborating across the University of South Dakota, Sanford School of Medicine, and South Dakota School of Mines & Technology. The position offers opportunities to work on translational biomedical research, developing intelligent systems for diagnostics, therapeutics, prognosis, and drug discovery, and to contribute to innovative research plans and publications.
Key responsibilities include developing and optimizing scalable machine learning models for biomedical and clinical research, collaborating with domain experts, contributing to publications and proposals, conceptualizing new research directions, and supporting reproducible research through well-documented code and workflows. Applicants should have a PhD or MS in Computer Science, Data Science, Artificial Intelligence, Biomedical Engineering, or a closely related field, with demonstrated research contributions. Required skills include proficiency in Python and ML libraries, data preprocessing, model evaluation, performance tuning, analytical thinking, and strong communication abilities. Preferred qualifications include experience with biomedical/clinical applications, high-performance computing, explainable AI, federated learning, collaborative grant-funded research, and a proven track record of research excellence.
The position is funded by the U.S. Department of Education ($6.5M) and SDBOR ($0.746M), with potential for extension based on performance and continued funding. Applications are reviewed on a rolling basis until the position is filled. Interested candidates should submit a cover letter, resume, research statement, publication samples, and references via the USD online employment portal. Early inquiries via email are encouraged.
For more information, visit the AI Research Lab website or contact Dr. KC Santosh, Professor and Chair of Computer Science, AI Lead, and Principal Investigator for SDBCC.
Funding
This is a full-time, grant-funded research position supported by the U.S. Department of Education ($6.5M) and SDBOR ($0.746M). The position offers competitive funding with the potential for extension based on performance and continued funding. Details on stipend or salary are not specified.
How to apply
Submit a cover letter (max 2 pages), resume, research statement (1 page), two publication sample copies, and contact information for three professional references via the University of South Dakota’s online employment portal at www.yourfuture.sdbor.edu. Early email inquiries are encouraged. Applications are reviewed on a rolling basis until filled.
Requirements
Applicants must have a PhD in Computer Science, Data Science, Artificial Intelligence, Biomedical Engineering, or a closely related discipline, or an MS in one of these fields with substantial, demonstrated contributions to biomedical research and innovation. Required skills include proficiency in Python and common machine learning libraries (e.g., scikit-learn, PyTorch, TensorFlow, JAX), experience with data preprocessing, model evaluation, and performance tuning, strong analytical thinking, collaborative skills, interdisciplinary collaboration, and written/verbal communication abilities. Preferred qualifications include experience with biomedical/clinical applications (medical imaging, informatics, omics data), familiarity with high-performance computing or cloud platforms, knowledge of explainable AI, federated learning, or trustworthy AI in healthcare, experience with collaborative grant-funded research and manuscript preparation, a proven track record of research excellence, and success with research grant applications.
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