Postdoctoral Fellow
One bioinformatics postdoctoral scholar position is available immediately through Baylor College of Medicine at the Neurological Research Institute (NRI). The postdoctoral scholar will be a part of the laboratory of Dr. Zhandong Liu. Primary responsibilities include development of novel bioinformatics algorithms to integrate multiple types of high-throughput genomics, transcriptomic, and proteomic data. The successful candidate will also be expected to work closely with wet-lab bench scientists. This postdoctoral position is available as part of a four-year research project with specific goals of developing novel methods for integrative analysis of high-throughput genomics data.
Environment:
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. Website: http://www.nri.texaschildrens.org/index.aspx
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 multi-omics data and is especially interested in addressing fundamental biological questions through machine learning and mathematical modeling approaches. Website: http://www.liuzlab.org/
Requirements:
The candidate should have (1) a PhD in Bioinformatics, Biostatistics, Computer Science, Statistics, or a related field, (2) strong mathematical/scientific programming skills in a language such as R or Matlab, and (3) experience with bioinformatics algorithms and large-scale data analysis. Proficiency in a language such as Python, JAVA, or C/C++ and/or experience with parallel programming is a plus. Some background in statistics, machine learning, and optimization is necessary, but the candidate will be given opportunities to expand their training in these areas if desired.
How To Apply: Please send a cover letter and CV via e-mail to my BCM email account.
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.
Requirements:
- B.S. or higher degree in Computer Science or relevant field
- Familiarity with UNIX-like environments and profound knowledge of HTTP
- Minimum one year of experience in 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 in 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 candidates 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 antone@bcm.edu.
Environment:
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.