Assistant Scientist - Nephrology - Quantitative Health

University of Florida; Gainesville (FL); Presencial; USD 70.000 - 110.000; Jornada completa

Descripción de la vacante

University of Florida in Gainesville invites applications for an Assistant Scientist in Nephrology - Quantitative Health. The role emphasizes deep learning, digital pathology, and multi-omics data integration, applying AI-driven image analysis to kidney disease research within CMIL led by Dr.

Pinaki Sarder. Candidates will work in a highly collaborative environment, developing scalable computational workflows for whole slide image analysis and contributing to advancing understanding of diabetic

Formación

• PhD in computer science, electrical engineering, biomedical engineering, or related field.

Responsabilidades

• Conduct cutting-edge research in deep learning, digital pathology, and multi-omics data integration.
• Collaborate with the Computational Microscopy Imaging Laboratory (CMIL) on kidney disease-focused projects.
• Develop scalable image analysis pipelines and contribute to AI-driven solutions for renal pathology.
• Publish results in peer-reviewed journals and present at conferences.
• Mentor junior researchers and contribute to grant writing and proposal development.

Conocimientos

Deep learning

PyTorch

TensorFlow

Image analysis

Python

Git / GitHub

HPC environments

Large-scale data processing

Educación

PhD in CS/EE/BME or related field

2–3 years postdoctoral experience

Herramientas

large_image (Kitware)

Git

GitHub

Descripción del empleo

Assistant Scientist - Nephrology - Quantitative Health

Job no: 540195
Work type: Non-Tenure-Track Faculty
Location: Main Campus (Gainesville, FL)
Categories: Medicine/Physicians
Department: 29051308 - MD-MED QUANTITATIVE HEALTH

Classification Title:

AST SCTST

Applicants must hold a PhD in computer science, electrical engineering, biomedical engineering, or a closely related field, and have completed at least 2–3 years of postdoctoral research experience. Candidates must also demonstrate a strong record of research productivity and scholarly achievement, as evidenced by peer-reviewed publications. Additionally, candidates must have:

• 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

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.

Research Focus Areas

• Computational pathology and digital pathology, with application to kidney disease and diabetic kidney disease
• Deep learning and AI model development for histological and microscopy image analysis
• Whole slide image (WSI) analysis and quantitative microscopy
• Spatial transcriptomics and multi-omics data integration
• High-performance computing and scalable biomedical data analysis pipelines

About the University of Florida

The University of Florida, a member of the Association of American Universities (AAU), is the largest and most comprehensive public university in the State of Florida, with large undergraduate, graduate, and postgraduate educational programs. The UF Health Science Center and its six colleges are co-located on the Gainesville campus, with additional teaching, research, and patient care sites in Jacksonville, Orlando, and other sites across Florida and internationally. Resources available for professional development include leadership, education, and research tracks within a Clinical and Translational Science Institute (CTSI), formal mentorship programs, and supported opportunities for teaching and research.

Salary is negotiable and commensurate with education and experience.

Applicants must hold a PhD in computer science, electrical engineering, biomedical engineering, or a closely related field, and have completed at least 2–3 years of postdoctoral research experience. Candidates must also demonstrate a strong record of research productivity and scholarly achievement, as evidenced by peer-reviewed publications. Additionally, candidates must have:

• 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

Preferred Qualification:

• 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

This requisition has been reposted. Previous applicants are still under consideration and need not apply.

Application must be submitted by 11:55 p.m. (ET) of the posting end date.

Health Assessment Required: No

Advertised: 04 Nov 2026 Eastern Standard Time
Applications close: 02 Dec 2026 Eastern Standard Time

The University of Florida is an Equal Employment Opportunity Employer.

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