University Of Texas Southwestern Medical Cent (The
Location
Dallas, TX
Job Type
UTSW-Taleo-External
Specialty
Research & Laboratory
Posted
2026-09-04
Applications close
2026-10-11
Job ID
23767005
Description
Computational Biologist II, Advanced Integrated Wet
Lab and Computational Researcher, Levi LabWHY 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 SUMMARYPerform professional work in support of scientific research using technical knowledge of software, software development, networking, and/or hardware in a complex computing environment. Subject matter expert in multiple areas of computing technology, and specific knowledge of molecular biology and genetics. Work collaboratively with Principal Investigator ("PI") to determine the most suitable computational methods and tools to analyze large-scale biological data sets. Prepare reports for presentation or publication. Responsible for assisting PI in meeting the system needs for multiple research projects and/or labs. This position is designed for an advanced scientist who can bridge wet-lab experimentation and independent computational analysis. The Computational Biologist II will help lead mechanistic and translational studies of injury, fibrosis, regeneration, aberrant mesenchymal cell fate, wound healing, tumor biology, and therapeutic response. The individual will work from study design and sample generation through data preprocessing, integration, biological interpretation, validation, and publication.LEVI LABORATORY RESEARCH PROGRAMThe 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, and multiomic technologies to identify mechanisms 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, and 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.ESSENTIAL JOB DUTIESDesign integrated experimental and computational strategies with the PI, clinical collaborators, and laboratory scientists, including sample selection, controls, replication, power considerations, batch mitigation, and validation plans.Independently analyze scRNA-seq, snRNA-seq, bulk RNA-seq, snATAC-seq or other epigenomic data, spatial transcriptomic data, proteomic and metabolomic data, CyTOF or high-parameter flow data, and quantitative imaging datasets from raw files through biological interpretation.Perform quality control, normalization, batch correction, cell-type annotation, differential analysis, pathway enrichment, trajectory and pseudotime analysis, gene-regulatory network inference, cell-cell communication modeling, ligand-receptor analysis, and cross-modality integration.Develop spatial and image-computational workflows for immunofluorescence, histology, multiplex imaging, micro
CT, confocal or whole-slide microscopy, and three-dimensional tissue datasets.Integrate experimental data with clinical variables, longitudinal outcomes, public datasets, and large multiomic databases to identify biomarkers, mechanisms, and therapeutic targets.Develop and rigorously evaluate statistical and machine-learning models for disease classification, early detection, risk prediction, treatment response, and biomarker prioritization, with appropriate feature selection, cross-validation, calibration, and external or biological validation.Build, document, test, and maintain reproducible analysis pipelines in R and Python using version control, workflow management, containerized environments, and high-performance or cloud computing resources.Establish laboratory standards for metadata, data dictionaries, sample tracking, file organization, quality metrics, code review, backup, controlled access, and FAIR data practices while complying with institutional and sponsor requirements.Perform or directly support wet-lab studies required to generate and validate computational findings, including animal handling, tissue harvest, cell and tissue dissociation, histology, immunostaining, imaging, cell culture, flow cytometry, nucleic acid isolation, PCR or qPCR, and sequencing-library workflows.Support transgenic colony studies, lineage-tracing experiments, injury and disease models, therapeutic perturbations, and collection of blood, skin, tendon, muscle, bone, tumor, lymphatic, and metastatic tissues.Translate computational hypotheses into targeted validation experiments using molecular assays, immunohistochemistry, CRISPR-Cas9 or other gene perturbation approaches, pharmacologic studies, and functional cellular or animal assays in collaboration with experimental scientists.Generate publication-quality visualizations and clear data narratives; lead computational sections of manuscripts, abstracts, grants, progress reports, and presentations; and contribute to high-impact peer-reviewed publications.Present findings at laboratory meetings and national or international scientific forums, communicate limitations and uncertainty clearly, and respond constructively to scientific review.Mentor trainees and staff in computational biology, experimental design, statistics, reproducible research, and biological interpretation, while contributing to a respectful, inclusive, and accountable laboratory culture.STRONGLY PREFERRED TECHNICAL EXPERTISEAdvanced proficiency in R and Python for biological data analysis, statistics, visualization, and pipeline development; experience with Linux, shell scripting, Git, and high-performance computing.Demonstrated hands-on experience analyzing single-cell transcriptomic datasets independently from raw-data processing and quality control through cell annotation, mechanistic interpretation, figure generation, and validation.Experience with spatial transcriptomics and at least one additional high-dimensional modality such as metabolomics, proteomics, epigenomics, CyTOF, imaging mass cytometry, or multiplex tissue imaging.Experience managing and integrating large clinical, imaging, or multiomic databases with robust metadata, reproducible provenance, and appropriate privacy and access controls.Strong foundation in molecular and cell biology, genetics, cancer or musculoskeletal biology, immunology, developmental biology, regenerative medicine, or a related field.Practical we
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