Post Doctoral Research Associates
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Job Location:
Arlington, TX - USA
Monthly Salary:
Not Disclosed
Posted on:
3 days ago
Vacancies:
1 Vacancy
Job Summary
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 Childrens Medical Center applying computational approaches to real-world clinical questions in pediatric precision oncology and treatment-related toxicities.
Essential Duties And Responsibilities
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 dataset. 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.
Required Qualifications
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
Preferred Qualifications
Network analysis Machine learning or AI methods using biological data Cancer genomics Large-scale genomic data analysis
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 Childrens Medical Center applying computational approaches to real-world clinical questions in pediatric precision oncology and treatment-related toxicities.
Essential Duties And Responsibilities
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 dataset. 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.
Required Qualifications
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
Preferred Qualifications
Network analysis Machine learning or AI methods using biological data Cancer genomics Large-scale genomic data analysis
Required Experience:
IC
Key Skills
About Company
An educational leader in the thriving North Texas region, UTA nurtures minds within an environment that values excellence, ingenuity, and diversity.
