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# Applied Machine Learning Postdoctoral Fellow

- **Company:** H. Lee Moffitt Cancer Center
- **Location:** Tampa, FL, United States
- **Salary:** $72,639 - $101,695
- **Contract:** Permanent contract
- **Skills:** Training Data, Artificial Intelligence, Data Analysis, Bioinformatics, Computational Biology, Computer Simulation, Computer Programming, Computer Engineering, Data Files, Data Integration, Data Mining, Python (Programming Language), Machine Learning, Tensorflow, Pytorch, Large Language Models, Deep Learning, Information Technology, Transformer Architectures, Feature Extraction
- **Published:** November 11, 2026
- **Apply:** https://www.careerbuilder.com/job-details/applied-machine-learning-postdoctoral-fellow-tampa-fl--6055d883-a78a-4e8d-8063-bf0db495a8b3

## About the Role

Machine Learning, Cancer, Data Sets, Genomics, Machine Learning, Biomedicine, Data Science, Predictive Modeling, Training Data Sets, Artificial Intelligence (AI), * 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, with an interest in interdisciplinary and collaborative research., * 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.
 * Excellent written and verbal communication skills and the ability to work effectively in a collaborative, interdisciplinary research environment.

## Description

* 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 and contribute to the preparation of manuscripts, reports, and funding applications.