Assistant Scientist - Nephrology - Quantitative Health

Quantitative Health • Gainesville, FL

4h • Onsite

About The Position

The Department of Medicine at the University of Florida invites applications for a full-time, non-tenure-track faculty position at the Assistant Scientist level. The successful candidate will join the Computational Microscopy Imaging Laboratory (CMIL), directed by Dr. Pinaki Sarder, a research group at the forefront of computational pathology, artificial intelligence, and microscopy image analysis applied to biomedical discovery. The successful candidate will contribute to cutting-edge research at the intersection of deep learning, digital pathology, and multi-omics data integration, with a strong emphasis on kidney disease, particularly, diabetic kidney disease. The position offers an exceptional opportunity to work in a highly collaborative, team-based research environment and to play a meaningful role in advancing AI-driven solutions for understanding complex renal pathologies.

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, as evidenced by peer-reviewed publications.
• Demonstrated expertise in deep learning and AI frameworks (e.g., PyTorch, TensorFlow) and large-scale image analysis libraries (e.g., 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 (e.g., Git/GitHub).
• Experience with high-performance computing (HPC) environments and large-scale data processing.

Nice To Haves

• Prior research experience in kidney disease, with specific expertise in diabetic kidney disease highly preferred.
• 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, with a collaborative research approach.

Responsibilities

• Contribute to cutting-edge research at the intersection of deep learning, digital pathology, and multi-omics data integration, with a strong emphasis on kidney disease, particularly, diabetic kidney disease.
• Advance AI-driven solutions for understanding complex renal pathologies.

Benefits

• Leadership, education, and research tracks within a Clinical and Translational Science Institute (CTSI)
• Formal mentorship programs
• Supported opportunities for teaching and research

What This Job Offers

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