Postdoctoral Research Associate-Computational Biology
Core
Conduct hypothesis-driven computational research on large-scale sequencing data to formulate quantitative models and publish primary research articles.
Role type
Postdoctoral Research Associate (Computational Biology)
Builds
Primary research articles and quantitative models from high-throughput sequencing datasets
Domain
Academic research, genomics, bioinformatics
Deliverable
production ML models
Required skills
hypothesis-driven research, large-scale sequencing data analysis, quantitative modeling, high-throughput sequencing data processing, software development, data management, pipeline development, statistical analysis, machine learning, team collaboration
Preferred skills
PhD in Computational Biology/Bioinformatics/Computer Science, UNIX/Linux environment programming, high-performance computing experience, data management best practices, inferential statistics expertise, innovative analytical approach design
Technologies
Python, R, Perl, Matlab, GitHub, UNIX/Linux, high-performance computing clusters
Responsibilities
Perform hypothesis-driven computational research with controls; analyze large-scale sequencing data and formulate quantitative models; interpret data and explain results in research discussions; implement tools to process, integrate, and visualize high-throughput sequencing datasets; collaborate with labs to design experiments and analyze datasets; present work at meetings and conferences; maintain and update software on TAMU cluster; contribute to code base with version control; supervise undergraduate and/or graduate students
Seniority
Postdoctoral Research Associate
