Bioinformatics Programmer II - Genomics of Fusion Oncoproteins Job at Baylor College of Medicine, Houston, TX

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  • Baylor College of Medicine
  • Houston, TX

Job Description

Summary

The Eagen Lab at Baylor College of Medicine is recruiting a highly motivated Bioinformatics Programmer II. This individual will advance research on how fusion oncoproteins regulate chromatin structure and gene expression. The position involves developing computational solutions at the interface of genomics, epigenetics, and cancer biology.

 

The Bioinformatics Programmer will apply open-source software and build customized pipelines for next-generation sequencing data analysis. This includes Hi-C, Micro-C, CUT&RUN, RNA-seq, and/or Perturb-seq datasets, as well as third-generation sequencing datasets such as long-read and single-molecule sequencing. The role offers an opportunity to build computational skills, contribute to high-impact research publications, and collaborate within an interdisciplinary and dynamic research team.

 

The Eagen Lab investigates 3D genome organization in cancer and discovered that the BRD4-NUT fusion oncoprotein reorganizes DNA folding to drive oncogenic transcription. The lab’s work has appeared in journals such as Molecular Cell, Nature Genetics, and Cancer Research, and earned recognition from the NIH Director, the National Cancer Institute, and the Cancer Prevention and Research Institute of Texas.

 

Baylor College of Medicine, ranked among the nation’s top medical schools, offers a collaborative research environment within the Texas Medical Center — the world’s largest biomedical campus. The position offers broad exposure to computational biology, bioinformatics, and biostatistics, with opportunities to develop pipelines and custom analyses using languages such as Python, R, and Shell scripting on Linux/Unix high-performance computing (HPC) systems. 

Job Duties

• Manage and analyze next-generation sequencing datasets, including Hi-C, Micro-C, Perturb-seq, CUT&RUN, ChIP-seq, and/or RNA-seq.
• Apply and/or develop appropriate statistical, machine learning, or computational analysis methods for large genomics datasets.
• Analyze third-generation sequencing data, including long-read (e.g. Oxford Nanopore, PacBio) and single-molecule sequencing datasets, as applicable to chromatin structure, transcriptome profiling, and fusion oncoprotein research.
• Collaborate closely with wet lab scientists to refine and integrate multi-omics analyses.
• Develop new computational and visualization tools to advance data interpretation.
• Maintain accurate records of computational workflows, code, and analyses to ensure reproducibility.
• Co-author scientific manuscripts and contribute to data figures and visualizations.
• Participate in lab meetings, contribute to scientific discussions, and maintain high standards of scientific rigor.
• Perform additional duties as assigned.

Minimum Qualifications

  • Bachelor's degree in Computer Science, Biological Science, or a related field. 
  • Two years of relevant experience.

     

Preferred Qualifications

  • Master’s degree in a related field.
  • Experience with Linux/Unix operating systems and cluster computing (e.g., SLURM).
  • Proficiency in Python, Shell scripting, and R.
  • Experience with open-source bioinformatics tools and pipelines.
  • Hands-on experience analyzing Hi-C, Micro-C, CUT&RUN, ChIP-seq, and/or RNA-seq datasets.
  • Experience analyzing third-generation sequencing data (e.g. isoform detection using long-read technologies or single-molecule epigenomic profiling).
  • Strong problem-solving skills with demonstrated ability to take initiative.
  • Ability to work independently and collaboratively in a fast-paced research environment.

 

 

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.

 

 

 

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