Advanced Integrated Wet-Lab and Computational Reseacher, Levi Lab

Job Description - Advanced Integrated Wet-Lab and Computational Reseacher, Levi Lab (968584) Job Description Advanced Integrated Wet-Lab and Computational Reseacher, Levi Lab - ( 968584 ) Description Computational Biologist II, Advanced Integrated Wet-Lab and Computational Researcher, 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!

Perform 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.

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, 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.

• Design 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 pseudo time 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…