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Software Engineer/Programmer

About the position:

A software engineer/programmer position is immediately available at the lab of Dr. Zhandong Liu from the Baylor College of Medicine at the Neurological Research Institute (NRI). Primary responsibilities include the development and maintenance of applications needed. The successful candidate will be expected to work closely with bioinformatics analysts and researchers.


  • B.S. or higher degree in Computer Science or relevant field
  • Familiarity with UNIX-like environment and profound knowledge on HTTP
  • Minimum one year of experience of full-stack development. Current tech stack includes:
    • HTML/CSS, Angular
    • JavaScript (ES6)
    • MongoDB, MySQL
    • R, Python
  • Understanding of data structures and algorithms 
  • Strong communication skills

Preferred Skills and Experience:

  • Experience in Amazon Web Services
  • Experience of full-stack development in a professional environment
  • Minimum one year of experience in scripting language Python, Perl, or equivalent
  • Familiarity with bioinformatics tools and biomedical sciences databases
  • Basic knowledge of statistics and machine learning
  • Excellent focus and management of tasks from multiple concurrent projects

The position is open for the candidate from all levels, and salary will be compensated according to qualifications.

Application Process:  

Email a cover letter and CV to zhandonl@bcm.edu and please CC yingwoow@bcm.edu.


The NRI brings together world experts in neuroscience, computer science, and applied mathematics to pursue collaborative, interdisciplinary basic and translational research on a variety of neurological and neurodevelopmental disorders. Please visit http://www.nri.texaschildrens.org to find out more.

At the NRI, the laboratory of Dr. Zhandong Liu focuses on the integrative modeling of transcription and signaling pathway activation. The lab develops algorithms for the analysis of gene expression arrays and next-generation sequencing data and is especially interested in addressing fundamental biological questions through machine learning and mathematical modeling approaches. Please visit liuzlab.org to find out more.