AI Research Scientist

Towson; Richmond (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

Massey Comprehensive Cancer Center's Bioinformatics Shared Resource seeks an AI Research Scientist to develop and deploy ML, DL, and large language models for cancer research. You will bridge bioinformatics and software engineering, deploying AI-enabled pipelines on HPC and cloud platforms.

Collaborate with investigators across multi-omics, digital pathology, and precision oncology, translating cancer questions into scalable, reproducible AI solutions within a shared-resource environment.

Qualifications

• Ph.D. in bioinformatics, computer science, biomedical informatics, computational biology, artificial intelligence, data science, or a closely related field or equivalent combination of education, experience, and training.
• At least 2 years of demonstrated experience in machine learning and deep learning.
• At least 2 years of experience working with large language models, including model evaluation, prompt design, retrieval-augmented generation, fine-tuning, agentic systems, or model deployment.
• Strong programming skills in Python and experience with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or comparable platforms.
• Experience deploying computational models or applications on high-performance computing clusters and/or cloud environments.

Responsibilities

• Develop, adapt, and evaluate machine learning and deep learning approaches for cancer genomic, transcriptomic, single-cell, spatial omics, imaging, and other high-dimensional datasets.
• Fine-tune, evaluate, and deploy large language models and biomedical foundation models for cancer research applications, including data interpretation, knowledge integration, and scientific workflow support.
• Develop AI agents and language model-based systems to support cancer bioinformatics analysis, research navigation, workflow automation, and scientific decision-making.
• Build full-stack applications integrating AI models, bioinformatics workflows, databases, visualization tools, APIs, and user-facing interfaces.
• Deploy and optimize AI models and computational workflows on institutional high-performance computing clusters and cloud platforms, and develop scalable training, inference, model-serving, and data-processing pipelines.
• Consult with Massey investigators on study design, project scoping, analytical strategy, data interpretation, and application of AI to cancer research questions.
• Collaborate on cancer-focused studies involving multi-omics, tumor microenvironment, spatial biology, digital pathology, precision oncology, and related areas.
• Develop, validate, document, and maintain reproducible AI and bioinformatics workflows that can be incorporated into ongoing Bioinformatics Shared Resource services.
• Evaluate model accuracy, robustness, reproducibility, computational efficiency, and suitability for cancer research applications.
• Provide technical guidance and training to BISR staff, trainees, and investigators in the appropriate use of AI-enabled computational approaches.
• Contribute to manuscripts, grant proposals, scientific presentations, progress reports, and dissemination of software and analytical methods.

Skills

Python

PyTorch

TensorFlow

JAX

Cloud deployment

HPC

Bioinformatics

Communication

Education

Ph.D. in bioinformatics or related field

Tools

Docker

Kubernetes

APIs

Databases

Version control

Job description

The Bioinformatics Shared Resource at Massey Comprehensive Cancer Center is seeking an AI Research Scientist to develop and deploy advanced machine learning, deep learning, and large language model solutions for cancer research. The ideal candidate will combine strong bioinformatics expertise with full-stack development and HPC/cloud deployment experience and will help expand AI-enabled research capabilities in support of Massey's Data to Discovery initiative.

Position Summary

The Bioinformatics Shared Resource at Massey Comprehensive Cancer Center is seeking a highly motivated AI Research Scientist to strengthen the cancer center's capabilities in artificial intelligence and to accelerate the use of AI across cancer research.

The successful candidate will work at the intersection of artificial intelligence, bioinformatics, and software engineering to develop, adapt, fine-tune, and deploy machine learning, deep learning, large language models, and biomedical foundation models for cancer-focused applications. The position will support research spanning cancer genomics, single-cell and spatial biology, multi-omics, tumor microenvironment studies, digital pathology, and precision oncology.

As a core member of the Bioinformatics Shared Resource, the scientist will work closely with basic, translational, and clinical investigators to translate cancer research questions into scalable, reproducible AI-enabled computational solutions. The position will also help build the infrastructure and expertise needed to advance Massey's Data to Discovery pillar.

Key Responsibilities

• Develop, adapt, and evaluate machine learning and deep learning approaches for cancer genomic, transcriptomic, single-cell, spatial omics, imaging, and other high-dimensional datasets.
• Fine-tune, evaluate, and deploy large language models and biomedical foundation models for cancer research applications, including data interpretation, knowledge integration, and scientific workflow support.
• Develop AI agents and language model-based systems to support cancer bioinformatics analysis, research navigation, workflow automation, and scientific decision-making.
• Build full-stack applications integrating AI models, bioinformatics workflows, databases, visualization tools, APIs, and user-facing interfaces.
• Deploy and optimize AI models and computational workflows on institutional high-performance computing clusters and cloud platforms, and develop scalable training, inference, model-serving, and data-processing pipelines.
• Consult with Massey investigators on study design, project scoping, analytical strategy, data interpretation, and application of AI to cancer research questions.
• Collaborate on cancer-focused studies involving multi-omics, tumor microenvironment, spatial biology, digital pathology, precision oncology, and related areas.
• Develop, validate, document, and maintain reproducible AI and bioinformatics workflows that can be incorporated into ongoing Bioinformatics Shared Resource services.
• Evaluate model accuracy, robustness, reproducibility, computational efficiency, and suitability for cancer research applications.
• Provide technical guidance and training to BISR staff, trainees, and investigators in the appropriate use of AI-enabled computational approaches.
• Contribute to manuscripts, grant proposals, scientific presentations, progress reports, and dissemination of software and analytical methods.

Required Qualifications

• Ph.D. in bioinformatics, computer science, biomedical informatics, computational biology, artificial intelligence, data science, or a closely related fieldor equivalent combination of education, experience, and training
• At least 2 years of demonstrated experience in machine learning and deep learning.
• At least 2 years of experience working with large language models, including model evaluation, prompt design, retrieval-augmented generation, fine-tuning, agentic systems, or model deployment.
• Strong programming skills in Python and experience with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or comparable platforms.
• Experience deploying computational models or applications on high-performance computing clusters and/or cloud environments.
• Experience with modern software development, including backend services, APIs, databases, containers, version control, and full-stack application development.
• Ability to work independently while contributing effectively within a multidisciplinary cancer research and shared-resource environment.
• Strong written and verbal communication skills, including the ability to translate technical concepts for experimental, translational, and clinical cancer researchers.
• Demonstrated experience working in and fostering an environment of respect, professionalism and civility with a population of faculty, staff, and students from various backgrounds and experiences, or a commitment to do so as a staff member at VCU

Preferred Qualifications

• Experience applying AI or machine learning to cancer genomics, transcriptomics, single-cell data, spatial omics, biomedical imaging, digital pathology, or multi-omics integration.
• Experience with biomedical foundation models, transformer architectures, multimodal learning, graph neural networks, diffusion models, or other generative modeling approaches.
• Experience developing agentic AI systems, tool-using language models, or automated scientific analysis workflows.
• Experience with retrieval-augmented generation, vector databases, knowledge graphs, and biomedical or cancer knowledge resources.
• Experience with precision oncology, tumor microenvironment analysis, biomarker discovery, or other cancer-focused computational research.
• A record of scientific publications, open-source software development, or contributions to collaborative biomedical or cancer research.
• Experience supporting investigators through a research core, shared resource, or other collaborative scientific environment.

Research and Collaborative Environment

The Bioinformatics Shared Resource supports investigators across Massey Comprehensive Cancer Center and the broader VCU research community by providing expertise in cancer bioinformatics, computational biology, multi-omics analysis, single-cell and spatial biology, data integration, visualization, and emerging AI-enabled research methods.

The AI Research Scientist will join a multidisciplinary team and collaborate with experimental, translational, and clinical investigators on high-impact cancer research. The position offers an opportunity to help establish next-generation AI capabilities within the cancer center, create broadly useful computational platforms, and accelerate the translation of complex cancer data into biological and clinical insight.

Professional Expectations

The successful candidate will demonstrate scientific rigor, intellectual curiosity, strong collaborative skills, and a commitment to developing dependable and reproducible computational tools for cancer research. The individual will be expected to balance innovative AI research with the practical requirements of deployment, documentation, maintenance, data security, reproducibility, and user support in a shared-resource environment.