Data Scientist III, Mineral Metabolism, Levi Lab

WHY UT SOUTHWESTERN? With over 75 years of excellence in Dallas-Fort Worth, Texas, UT Southwestern is committed to excellence, innovation, teamwork, and compassion. As a world-renowned medical and research center, we strive to provide the best possible care, resources, and benefits for our valued employees. Ranked as the number 1 hospital in Dallas-Fort Worth according to U.S. News & World Report , we invest in you with opportunities for career growth and development to align with your future goals. Our highly competitive benefits package offers healthcare, PTO and paid holidays, on-site childcare, wage, merit increases and so much more. We invite you to be a part of the UT Southwestern team where you'll discover a culture of teamwork, professionalism, and a rewarding career! JOB SUMMARY Works under broad direction to provide and oversee the analysis and development of algorithms and software for clinical and/or basic research problems. Oversees and participates in programs to impact data acquisition, management, and analysis in basic, translational, and clinical research, including clinical trials. Perform advanced professional work in support of biomedical and translational research using advanced expertise in one or more of the following areas: bioinformatics, quantitative image analysis, or machine learning. Collaborate with the Principal Investigator, laboratory scientists, clinicians, and multidisciplinary partners to design rigorous analytic strategies; analyze complex biomedical datasets within the candidate’s area of expertise; and deliver reproducible analyses, publication-quality figures, manuscripts, presentations, and grant materials. Candidates are not expected to have expertise in all three areas or in every data type used by the laboratory. This position is designed for a senior data scientist who can independently lead the analytic components of multiple research programs from study design and data acquisition through quality control, modeling, biological interpretation, validation, and dissemination. The Data Scientist III will support mechanistic and translational studies of injury, fibrosis, regeneration, aberrant mesenchymal cell fate, wound healing, tumor biology, and therapeutic response. The role is primarily computational, with close collaboration with experimental and clinical teams to ensure that analyses are biologically grounded and directly responsive to clinically important questions. LEVI LABORATORY RESEARCH PROGRAM The Levi Laboratory studies how immune, stromal, vascular, lymphatic, neural, epithelial, and mesenchymal cell populations interact after injury and in disease. The laboratory integrates transgenic and surgical animal models, human biospecimens, molecular and cellular biology, quantitative imaging, clinical data, and multiomic technologies to identify mechanisms, biomarkers, and therapies that promote faithful tissue repair. • Traumatic heterotopic ossification and aberrant mesenchymal differentiation after burns, musculoskeletal trauma, surgery, and tendon injury. • Fibrosis, wound healing, burn and scar biology, including inflammatory and epigenetic regulation of keratinocyte, fibroblast, immune, and progenitor-cell function. • Tendon, muscle, bone, and soft-tissue repair, including mechanotransduction, extracellular matrix remodeling, and stem or progenitor-cell fate. • Neurovascular and neuroimmune regulation of regeneration, tendinopathy, heterotopic ossification, pain, osteosarcoma, and adrenergic signaling. • Lymphatic regulation of inflammation, tissue repair, and bone resorption, including VEGF-C or VEGF-D signaling and lymphatic endothelial-cell biology. • Immunometabolism and obesity-related injury responses, including lipid metabolism, inflammatory signaling, and altered regenerative cell states. • Circulating mesenchymal progenitor cells and liquid-biopsy approaches for early diagnosis, risk prediction, and treatment monitoring. • Cancer biology and osteosarcoma, including tumor heterogeneity, tumor microenvironment interactions, angiogenesis, pain, drug response, and pulmonary metastasis. SPECIFIC JOB DUTIES • Lead the design of data-driven research strategies with the PI, clinical collaborators, and laboratory scientists, including outcome definition, sample selection, controls, replication, power considerations, data harmonization, batch mitigation, and validation plans. • Independently analyze complex biomedical datasets from raw files through final biological and clinical interpretation within one or more areas of expertise: bioinformatics, quantitative image analysis, or machine learning. Relevant datasets may include single-cell or bulk transcriptomic, epigenomic, spatial, proteomic, metabolomic, high-parameter cytometry, imaging, micro-CT, or clinical data. Assignments will reflect the candidate’s expertise and project needs; experience with all listed modalities is not required. • For bioinformatics-focused projects, perform and document analyses appropriate to the data and research question, such as quality control, normalization, batch correction, cell-type annotation, differential analysis, pathway enrichment, trajectory analysis, gene-regulatory network inference, cell-cell communication modeling, or cross-modality integration. • For image-analysis-focused projects, develop scalable workflows for relevant imaging data, such as histology, immunofluorescence, multiplex imaging, confocal microscopy, whole-slide imaging, micro-CT, or three-dimensional tissue datasets, including segmentation, feature extraction, spatial quantification, and visualization as appropriate. • Where relevant to the candidate’s expertise and project goals, integrate experimental data with clinical variables, longitudinal outcomes, public datasets, or multiomic databases to identify biomarkers, mechanisms, therapeutic targets, and clinically meaningful patient subgroups. • For statistical-modeling or machine-learning-focused projects, devel