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Computational Biology Research Associate

Singh Laborator
Texas (USA)
Commensurate with experience
Closing date
Nov 10, 2022
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A Research Associate position in computational biology is available in the Singh laboratory at Department of Molecular and Cellular Medicine, Texas A&M University Health Science Center. The laboratory applies and develops computational biology approaches to understand regulatory mechanisms in normal and diseased states. The primary focus of our group is to utilize diverse, high-throughput functional assays and next-generation sequencing approaches to uncover mechanisms of transcriptional and co-transcriptional regulation. We combine the strengths of computational methods and molecular assays to dissect the functional regulatory programs in mammalian cells.

The Research Associate will analyze and interpret the large-scale sequencing datasets that are being generated from animal models and patient samples. This is an excellent opportunity for a candidate with background in biology and experience in computer science or statistics who is enthusiastic about learning how to integrate high throughput datasets to facilitate understanding of transcriptional and epigenetic regulation. The Research Associate will work in direct supervision of Dr. Irtisha Singh, who has extensive experience in analysis and interpretation of large-scale sequencing datasets. The candidate will participate in on-going collaborations with oncologists which will require analysis of high-throughput patient data like ATAC-seq, ChIP-seq, RNA-seq and single-cell RNA-seq.

Preferred Education: Recent PhDs with strong publications in computer science, bioinformatics, computational biology, machine learning and related fields will be considered. Training in statistics, and programming experience in a UNIX/Linux environment using programming languages such as Python, R, and/or Perl is required.

Preferred Experience: Experience in high-throughput analysis of next-generation sequencing data, familiarity with cluster computing and widely-used consortium datasets are advantageous. The candidate must have excellent verbal and written communication skills – in English – and be capable of working within a team of wet and dry lab researchers.

Preferred Special Knowledge, Skills, and Abilities: The candidate should have expertise in computational biology and is expected to devise innovative analytical approaches to high-volume genomic, epigenomic, and gene expression data. The successful candidate will work independently and take a leading role in data analysis, interpretation, and visualization, and drafting of manuscripts for publication.

Application information:

  • Review of applications will begin immediately. Applications will be considered on a rolling basis. 
  • Please send your CV, relevant publications, and list of three referee to Dr. Singh .
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