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Spatial Transcriptomics Jobs in Florida (NOW HIRING)

UAB

RESEARCHER LEAD

Tampa, FL

By integrating cancer biology, neuroscience, extracellular matrix (ECM) biology, spatial transcriptomics, advanced imaging, and immunology, we aim to identify novel therapeutic strategies for ...

The University of Miami

Research Associate 2

Miami, FL · On-site

Analyze high-throughput sequencing datasets (e.g., RNA-seq, ChIP-seq, ATAC-seq, scRNA-seq, scATAC-seq, Hi-C, and spatial transcriptomics), apply statistical modeling and machine learning, and develop ...

University of Miami

Research Associate 2

Miami, FL · On-site

Analyze high-throughput sequencing datasets (e.g., RNA-seq, ChIP-seq, ATAC-seq, scRNA-seq, scATAC-seq, Hi-C, and spatial transcriptomics), apply statistical modeling and machine learning, and develop ...

The University of Miami

Entry Scientist

Miami, FL · On-site

Apply spatial transcriptomics, spatial proteomics, and advanced imaging techniques to postmortem brain tissues. Data Analytics & Bioinformatics * Integrate and analyze complex datasets using data ...

University of Miami

Entry Scientist

Miami, FL · On-site

Apply spatial transcriptomics, spatial proteomics, and advanced imaging techniques to postmortem brain tissues. Data Analytics & Bioinformatics * Integrate and analyze complex datasets using data ...

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Spatial Transcriptomics information

What is spatial transcriptomics?

Spatial transcriptomics is an advanced technique that allows scientists to measure gene expression within the spatial context of tissue samples. Unlike traditional RNA sequencing, which loses information about where each gene is expressed, spatial transcriptomics preserves the physical location of gene activity in tissues. This helps researchers better understand how cells function within their native environments and interact with neighboring cells, which is especially valuable in fields like cancer research, neuroscience, and developmental biology. The method combines microscopy, molecular biology, and computational analysis to produce detailed maps of gene expression.

What are the key skills and qualifications needed to thrive as a spatial transcriptomics scientist?

To thrive as a Spatial Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree in a life science field. Familiarity with spatial transcriptomics platforms (such as 10x Genomics Visium), next-generation sequencing (NGS) technologies, and data analysis tools like R or Python is essential. Strong problem-solving skills, attention to detail, and effective communication are important soft skills for collaborating on interdisciplinary research projects. These skills and qualities are crucial for generating high-quality spatial gene expression data and translating findings into meaningful biological insights.

What are some common challenges faced by professionals working in spatial transcriptomics, and how can they be addressed?

Professionals in spatial transcriptomics often encounter challenges related to handling large, complex datasets and integrating spatial information with gene expression data. Ensuring high-quality sample preparation and mastering advanced imaging or sequencing technologies are also frequent hurdles. These challenges can be addressed by collaborating closely with multidisciplinary teams—including bioinformaticians, molecular biologists, and imaging specialists—and staying up-to-date with the latest software tools and protocols. Continuous learning and effective communication within the team are key to overcoming technical and analytical obstacles in this rapidly evolving field.

What are popular job titles related to Spatial Transcriptomics jobs in Florida?

For Spatial Transcriptomics jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Spatial Transcriptomics jobs in Florida look for?

The top searched job categories for Spatial Transcriptomics jobs in Florida are:

What cities in Florida are hiring for Spatial Transcriptomics jobs?

Cities in Florida with the most Spatial Transcriptomics job openings:

Spatial Transcriptomics jobs near you
Infographic showing various Spatial Transcriptomics job openings in Florida as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Research Assistant Scientist

University of Florida

Gainesville, FL • On-site

Full-time

Re-posted 18 days ago

University Of Florida rating

7.2

Company rating: 7.2 out of 10

Based on 108 frontline employees who took The Breakroom Quiz

385th of 623 rated colleges and universities

Job description

Research Assistant Scientist
Job no: 540847
Work type: Non-Tenure-Track Faculty
Location: Main Campus (Gainesville, FL)
Categories: Medicine/Physicians
Department:29080100 - MD-PATHOLOGY-GENERAL
Classification Title:Research Assistant Scientist
Classification Minimum Requirements:
  • Ph.D. in Computer Science, Biomedical Informatics, Data Science, Biomedical Engineering, Electrical Engineering, Bioinformatics, Statistics, Applied Mathematics, Physics, or a closely related STEM field.
  • Demonstrated experience developing AI and machine learning models for biomedical applications.

Job Description:
The University of Florida Diabetes Institute (UFDI) invites applications for a full-time, non-tenure-track Assistant Scientist to join an interdisciplinary research environment focused on advancing the prevention, prediction, and treatment of diabetes through artificial intelligence, computational biology, and precision medicine. The successful candidate will contribute to the development and application of innovative AI and machine learning approaches that accelerate discovery across basic, translational, and clinical diabetes research
Research efforts may support initiatives such as:
  • AI-enabled discovery of novel diabetes therapies
  • Precision medicine for Type 1 and Type 2 diabetes
  • Human pancreas imaging and spatial biology
  • Digital pathology and computational tissue analysis
  • Clinical decision support using EHR data
  • Translational validation using human biospecimens and experimental model system
  • Artificial intelligence and machine learning for diabetes research, including Type 1 and Type 2 diabetes
  • Computational pathology and digital pathology using whole slide imaging (WSI)
  • Spatial biology, spatial transcriptomics, and multi-omics data integration
  • Large language models (LLMs) and foundation models for biomedical research
  • Electronic Health Record (EHR) analytics and clinical data integration
  • Biomedical image analysis and quantitative microscopy
  • High-performance computing (HPC) and scalable AI pipelines
  • Development of reproducible software tools and computational workflows for biomedical research

Develop novel AI, machine learning, and deep learning methods to address complex biomedical questions in diabetes.
Design and implement computational tools for integrating imaging, genomic, transcriptomic, proteomic, metabolomic, and clinical datasets.
Develop scalable software applications and maintain research code using modern software engineering practices.
Apply AI methods to whole slide images, microscopy datasets, spatial transcriptomics, and EHR-derived clinical data.
Collaborate with multidisciplinary teams of clinicians, computational scientists, engineers, statisticians, and laboratory investigators.
Lead and participate in collaborative research projects spanning basic science, translational research, and clinical applications.
Prepare scientific manuscripts, conference presentations, and competitive grant applications.
Mentor graduate students, postdoctoral fellows, research staff, and trainees.
Expected Salary:
Commensurate with education and experience
Required Qualifications:
  • Ph.D. in Computer Science, Biomedical Informatics, Data Science, Biomedical Engineering, Electrical Engineering, Bioinformatics, Statistics, Applied Mathematics, Physics, or a closely related STEM field.
  • Demonstrated experience developing AI and machine learning models for biomedical applications.
  • Strong programming experience in Python and/or R.
  • Experience with Git/GitHub and collaborative software development.
  • Experience working in Linux and high-performance computing environments.
  • Evidence of scholarly productivity through peer-reviewed publications.

Preferred:
  • Experience applying AI or machine learning to diabetes, metabolic disease, immunology, or other complex biomedical diseases.
  • Experience with digital pathology, computational pathology, whole slide image analysis, or quantitative microscopy.
  • Experience integrating multi-modal datasets, including genomics, transcriptomics, spatial transcriptomics, proteomics, metabolomics, imaging, and EHR data.
  • Experience with modern deep learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, Pandas, NumPy, and SciPy.
  • Familiarity with convolutional neural networks (CNNs), graph neural networks (GNNs), transformer architectures, foundation models, and large language models (LLMs).
  • Experience developing reproducible biomedical software and AI workflows.
  • Demonstrated success contributing to grant proposals or securing research funding.
  • Experience mentoring students and junior investigators.

Special Instructions to Applicants:
In order to be considered, you must upload your cover letter and resume.
Applicants should apply online and include a curriculum vitae, a letter outlining interests, and three letters of reference. The letters may also be sent directly to Dr. Todd Brusko (tbrusko@ufl.edu), Search Committee Chair, and copy Stacey Oliver (oliversl@ufl.edu).
The successful candidate will be required to provide an official transcript to the hiring
department upon hire. A transcript will not be considered "official" if a designation of "Issued to
Student" is visible. Degrees earned from educational institutions outside of the United States must
be evaluated by a professional credentialing service provider approved by the National Association
of Credential Evaluation Services (NACES), which can be found at
http://www.naces.org/.
The Search Committee will accept applications until the position is filled. Applications will be reviewed on an ongoing basis by the committee.
Health Assessment Required:No
Advertised: 07 Aug 2026 Eastern Daylight Time
Applications close:
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About University of Florida

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The University of Florida is one of the top ranked public universities in the United States (ranked top 5 amongst public universities in 2023 US news and world report). It is one of only a few comprehensive universities, having medical, veterinary, dental, nursing, public health, and engineering disciplines all co-localized on the same, contiguous campus to facilitate interdisciplinary collaboration. Gainesville is located in the northern region of Florida, within 1-1.5 hours of each coast, and just 1.5-2 hours to Orlando and Tampa. It is a small to medium-sized city with a low cost of living, excellent public and private schools, and southern hospitality. While Gainesville is widely recognized as the home of the Gators, it is quickly becoming known as a center for innovation and a place with a lifestyle that's comfortable for families, yet attractive for young professionals.

Industry

Colleges, universities, and professional schools

Company size

5,001 - 10,000 Employees

Headquarters location

Gainesville, FL, US

Year founded

1853

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