Applied Machine Learning Postdoctoral Fellow

Moffitt

. Develop novel machine learning models for molecular and multi-omics data analysis, representation learning, and predictive modeling .

Posted 9/25/2026full-timeTampa • Florida • United StatesMid-LevelSenior💰 $72,639 - $101,695 per yearWebsite

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Develop novel machine learning models for molecular and multi-omics data analysis, representation learning, and predictive modeling
Develop methods for learning robust patient and molecular representations from large-scale genomic, transcriptomic, and other molecular profiling datasets
Design and implement scalable pipelines for molecular data integration, feature representation, and downstream machine learning applications
Investigate and apply advanced AI approaches, including foundation models, self-supervised learning, transformer architectures, graph-based methods, and other emerging machine learning techniques
Collaborate with researchers, clinicians, and data scientists on translational cancer research projects, scientific publications, and grant development
Present research findings at scientific meetings
Contribute to manuscripts, reports, and funding applications

Requirements

What you’ll need

Background in Computer Science, Electrical Engineering, Computer Engineering, Mathematics, Statistics, Physics, Data Science, Computational Biology, Bioinformatics, or a related quantitative discipline
Strong computing, programming, and analytical skills, preferably in Python and modern machine learning frameworks such as PyTorch
Experience with machine learning, deep learning, artificial intelligence, data mining, statistical modeling, or related computational methods
Interest in developing and applying advanced AI methods to large-scale molecular, genomic, clinical, or other biomedical datasets
Familiarity with representation learning, foundation models, transformer architectures, graph-based methods, self-supervised learning, or related machine learning techniques is desirable
Experience working with cancer, biological, molecular, or other real-world healthcare datasets is required
Strong written and verbal communication skills
PhD or equivalent degree in Computer Science, Computer Engineering, Electrical Engineering, Biomedical Engineering, Mathematics, Statistics, Physics, Data Science, Bioinformatics, Computational Biology, or a related quantitative discipline
Demonstrated research experience in machine learning, artificial intelligence, data science, computational biology, bioinformatics, or related fields
Strong publication record commensurate with career stage, including at least one first-author peer-reviewed publication, preprint, or equivalent research contribution
Experience with scientific programming and machine learning frameworks
Ability to work effectively in a collaborative, interdisciplinary research environment
Submit a single PDF containing a cover letter, personal statement, current CV with recent publications, and contact information for three references

Benefits

Comp & perks

Comprehensive medical coverage with Moffitt covering the premium effective the first day
Dental insurance
Vision insurance
Generous paid time off
Retirement benefits
Parental leave
Potential relocation assistance according to policy
State-of-the-art computational resources
Outstanding mentorship from expert faculty
Opportunities to publish in leading scientific venues
Opportunities to collaborate across disciplines
Opportunities to participate in competitive fellowship and grant applications