Post Doctoral Research Associates
Listed on 2026-05-16
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Research/Development
Data Scientist, Research Scientist, Clinical Research
Job Summary
The Department of Bioengineering in the College of Engineering at the University of Texas at Arlington invites applications for a Post-Doctoral Research Associate. We are seeking a highly motivated postdoctoral candidate with experience in cancer research and strong analytical skills. The Lal Lab develops computational and systems biology approaches to understand treatment response, toxicity, and disease progression in cancer. Our research integrates multi-omic sequencing, network biology, and machine learning to identify actionable biomarkers and therapeutic vulnerabilities.
The successful candidate will work at the interface of computational genomics, AI-driven modeling, and translational oncology, analyzing large-scale multi-omic datasets from pediatric cancer cohorts. The position offers a unique opportunity to collaborate closely with clinicians and translational researchers at Cook Children’s Medical Center, applying computational approaches to real-world clinical questions in pediatric precision oncology and treatment-related toxicities.
- Ph.D. in bioinformatics, computational biology, statistics, computer science, or related field
- Proficiency in R or Python
- Minimum of two years of experience in computational biology or cancer genomics
- Experience with high-performance or cloud computing (e.g., HPC, AWS, GCP)
- At least one first‑author peer‑reviewed publication
- Strong communication and scientific writing skills
- Network analysis
- Machine learning or AI methods using biological data
- Cancer genomics
- Large‑scale genomic data analysis
- Analyze large-scale next-generation sequencing (NGS) datasets, including whole genome/exome sequencing, RNA‑seq, and DNA methylation data.
- Develop and implement state‑of‑the‑art computational and statistical methods for integrative analysis of multi‑omics datasets.
- Utilize high-performance computing environments to process large-scale datasets and analyze large-scale genomics data.
- Collaborate closely with clinicians and experimental scientists to translate in silico results to biologically meaningful insights.
- Clearly present research findings to interdisciplinary collaborators.
- Prepare manuscripts for publications and contribute to grant proposals.
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