AI Research Scientist

AI Research Scientist 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. 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 include developing, adapting, and evaluating machine learning and deep learning approaches for cancer genomic, transcriptomic, single-cell, spatial omics, imaging, and other high-dimensional datasets; fine-tuning, evaluating, and deploying large language models and biomedical foundation models for cancer research applications; developing AI agents and language model-based systems to support cancer bioinformatics analysis, research navigation, workflow automation, and scientific decision-making; building full-stack applications integrating AI models, bioinformatics workflows, databases, visualization tools, APIs, and user-facing interfaces; deploying and optimizing AI models and computational workflows on institutional high-performance computing clusters and cloud platforms, and developing scalable training, inference, model-serving, and data-processing pipelines; consulting with Massey investigators on study design, project scoping, analytical strategy, data interpretation, and application of AI to cancer research questions; collaborating on cancer-focused studies involving multi-omics, tumor microenvironment, spatial biology, digital pathology, precision oncology, and related areas; developing, validating, documenting, and maintaining reproducible AI and bioinformatics workflows that can be incorporated into ongoing Bioinformatics Shared Resource services; evaluating model accuracy, robustness, reproducibility, computational efficiency, and suitability for cancer research applications; providing technical guidance and training to BISR staff, trainees, and investigators in the appropriate use of AI-enabled computational approaches; and contributing to manuscripts, grant proposals, scientific presentations, progress reports, and dissemination of software and analytical methods. Required qualifications include a 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; 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; and 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 include 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; and experience supporting investigators through a research core, shared resource, or other collaborative scientific environment. Salary range: starting at $100,000 - commensurate with experience. FLSA exemption status: exempt. Hours per week: 40. Restricted position: no. ORP eligible: yes. Flexible work arrangement: hybrid. University job title: Senior Scientist RS - Open. Virginia Department of Human Resource Management