Postdoctoral Associate

Division: Pathology


Work Arrangement: Onsite only


Location: Houston, TX


Salary Range: $63,480


FLSA Status: Exempt


Work Schedule: Monday - Friday, 8 a.m. - 5 p.m.


Summary


Postdoctoral positions in cheminformatics are available in the Zhi Tan laboratory at Baylor College of Medicine (Houston, TX), an interdisciplinary group using deep learning, computational chemistry, medicinal chemistry, chemical biology, and molecular cell biology to develop novel therapeutics to tackle complex diseases such as cancers. Postdoctoral Associate with a proven track record in developing open-source machine learning, deep learning, or cheminformatics tools.


Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates.

• Plans, directs and conducts research experiments.
• Develops research techniques and perform applications required for specific research projects.
• Conducts literature searches and summarize information in an appropriate format for a particular study.
• Documents results of experiments and reports to principal investigators.
• Performs other job-related duties as assigned.

• MD or Ph.D. in Basic Science, Health Science, or a related field.
• No experience required.

• Doctoral Degree in Computational Chemistry, bioinformatics, computational biology, or related discipline. Experience may not be substituted in lieu of degree.
• Experience in cheminformatics software development.
• Experience in developing machine learning, deep learning tools, especially with application in drug discovery.
• Experience with high performance computing environment (HPC) / cluster job submission.
• Knowledge of statistical methods, data science algorithms, scientific and numerical computation.
• Familiarity with common Python tools including Pandas, Numpy, Scipy, Django, RDKit.
• Proficiency in coding and debugging in Pytho.
• Strong knowledge and experience with relational databases (e.g. Oracle, SQL, MySQL).
• Comfortable working in a Linux environment.
• Experience with data processing pipelines and data analysis.
• Excellent communication skills with a diverse team of biological and chemical scientists.
• Experience with development of open-source computational tools (machine learning, deep learning, cheminformatics), especially with application in drug discovery.