Assistant Scientist - Nephrology - Quantitative Health

University of Florida • Gainesville, FL

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About The Position

The Department of Medicine at the University of Florida is hiring a full-time, non-tenure-track Assistant Scientist to join the Computational Microscopy Imaging Laboratory (CMIL), directed by Dr. Pinaki Sarder. CMIL conducts research in computational pathology, artificial intelligence, and microscopy image analysis for biomedical discovery.

The successful candidate will contribute to research at the intersection of deep learning, digital pathology, and multi-omics data integration, with an emphasis on kidney disease, particularly diabetic kidney disease. The role is part of a collaborative, team-based research environment focused on advancing AI-driven approaches to understanding complex renal pathologies. Research areas include computational and digital pathology, deep learning for histological and microscopy image analysis, whole slide image analysis, quantitative microscopy, spatial transcriptomics, multi-omics integration, and scalable biomedical data analysis pipelines using high-performance computing.

The University of Florida offers professional development resources, including leadership, education, and research tracks within its Clinical and Translational Science Institute, formal mentorship programs, and supported opportunities for teaching and research. Salary is negotiable and commensurate with education and experience.

Requirements

• PhD in computer science, electrical engineering, biomedical engineering, or a closely related field.
• At least 2–3 years of postdoctoral research experience.
• Strong record of research productivity and scholarly achievement, evidenced by peer-reviewed publications.
• Demonstrated expertise in deep learning and AI frameworks such as PyTorch or TensorFlow, and large-scale image analysis libraries such as large_image by Kitware.
• Hands-on experience with whole slide image analysis and computational pathology workflows.
• Proficiency in Python and scientific computing libraries.
• Experience with version control systems such as Git or GitHub.
• Experience with high-performance computing environments and large-scale data processing.

Nice To Haves

• Prior research experience in kidney disease, especially expertise in diabetic kidney disease.
• Experience with spatial transcriptomics and multi-omics data integration.
• Familiarity with microscopy imaging modalities relevant to renal pathology.
• Track record of or demonstrated potential for independent grant writing and funding acquisition.
• Experience mentoring junior researchers, graduate students, or undergraduate trainees.
• Strong written and verbal communication skills and a collaborative research approach.

Responsibilities

• Contribute to research in computational pathology, digital pathology, and kidney disease, particularly diabetic kidney disease.
• Develop deep learning and AI models for histological and microscopy image analysis.
• Conduct whole slide image analysis and quantitative microscopy research.
• Contribute to spatial transcriptomics and multi-omics data integration.
• Work with high-performance computing and scalable biomedical data analysis pipelines.
• Collaborate in an interdisciplinary, team-based research environment.

Benefits

• Professional development resources, including leadership, education, and research tracks within the Clinical and Translational Science Institute.
• Formal mentorship programs.
• Supported opportunities for teaching and research.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree