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3 дня назад

Postdoctoral Research Associate-Computational Biology

Формат работы
onsite
Тип работы
fulltime
Грейд
trainee
Английский
b2
Страна
US
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TL;DR
Postdoctoral Research Associate-Computational Biology (Computational Biology/Genomics): Conducting hypothesis-driven computational research and analyzing high-throughput sequencing data with an accent on quantitative modeling, data integration, and scientific communication. Focus on developing data-processing pipelines, maintaining research software on a high-performance computing cluster, and devising analytical approaches for genomic, epigenomic, and gene-expression data.

Location: Bryan, Texas, United States; work may extend beyond normal office hours and include weekends.

Company

Texas A&M University Health Science Center is an academic health center conducting transformative education, innovative research, and team-based health care delivery.

What you will do

  • Conduct hypothesis-driven computational research using controls, quantitative models, and large-scale sequencing data.
  • Implement, apply, evaluate, and maintain tools for processing, integrating, analyzing, and visualizing high-throughput sequencing datasets.
  • Interpret and communicate research findings through group meetings, primary research articles, scientific conferences, and research discussions.
  • Collaborate with TAMU laboratories and external collaborators to design experiments, analyze datasets, and develop innovative project approaches.
  • Maintain and update software on the TAMU cluster, contribute to the codebase, and maintain personal code in a GitHub or equivalent version-controlled repository.
  • Supervise undergraduate and/or graduate students and other laboratory, technical, or field staff involved in research.

Requirements

  • Appropriate PhD.
  • Ability to multitask and work cooperatively with others.

Nice to have

  • PhD in Computational Biology, Bioinformatics, or Computer Science.
  • Training in statistics and programming experience in a UNIX/Linux environment using Python, R, and/or Perl.
  • Experience analyzing genomic, transcriptomic, or epigenomic data, including RNA-seq, ATAC-seq, and ChIP-seq.
  • Experience working in a high-performance computing environment and developing data-management and data-processing pipelines.
  • Proficiency in R, Python, and/or Matlab.
  • Familiarity with software-development best practices, including unit testing and version control.
  • Familiarity with inferential statistics and machine learning.
  • Expertise in computational biology and the ability to devise innovative analytical approaches for high-volume genomic, epigenomic, and gene-expression data.
  • Ability to work within a team of wet- and dry-lab researchers.

Culture & Benefits

  • Grant-funded position; future employment may depend on future funding.
  • Medical, prescription drug, dental, vision, life, accidental death and dismemberment, flexible spending account, and long-term disability insurance, with Texas A&M contributing to employee health and basic life premiums.
  • 12–15 annual paid holidays, paid sick leave, and paid vacation.
  • Automatic enrollment in the Teacher Retirement System of Texas.
  • Free exercise programs, release time, LinkedIn Learning, professional-development support, educational release time, and tuition assistance.
  • Employment is subject to a criminal history investigation and credential verification.

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