Entry Level Bioinformatics Machine Learning Jobs

Our unique program focuses on how to interpret genetic variations that cause human diseases by leveraging protein structure-based simulations and calculations. We take a proteogenomic approach, developing the processes to apply computational biochemistry, computational biophysics, and more to individualize genomic data interpretation to specific clinical and research cases. The team leverages multi-disciplinary approaches, including Big Genomics Data, systems biology, computational biophysics, biochemistry, and structural protein bioinformatics, to develop a more comprehensive and integrated understanding of the underlying mechanisms of diseases. The successful candidate will join our productive team using our established computational structural genomics workflow and team-based process that we have developed. Specifically, we seek someone with experience using computational modeling tools (e.g., molecular dynamics simulations and molecular mechanics calculations) and, ideally, an understanding of genetics and molecular biology. The ability to effectively communicate within a diverse team is critical, including presenting findings, working collaboratively, generating publication-quality figures, adapting to priorities, discussing barriers to progress as they are identified, and being flexible regarding the technologies used so that we can efficiently accomplish our scientific and translational research goals.

• Understands principles of biomolecular structure, molecular simulations, and the interpretation of results. Independently provides troubleshooting for data generation and processing. Maintains a working understanding of principles in genetics, biochemistry, molecular biology, and biophysics.

• Develops, implements, and refines bioinformatic workflows and tools for analyzing and visualizing molecular simulation data. Runs standardized workflow for annotating protein and biomolecular structures.

• Leads the analysis and writing for a portfolio of modeling projects, prioritized by the team and Director. Implements triaging workflow and generates reports. Contributes to collaborative research publications. Presents regular project updates at team meetings and with collaborators.

• Adapts bioinformatics tools, visualization packages, and annotation resources to perform research analysis independently and accurately - flexibility and competency in data wrangling.

• Development of automated analysis methods to assess model quality, computed features, and analyze MD simulations. Statistical mechanics and machine learning preferred.

• Excellent written and verbal communication skills to present analysis to our group and externally, through research presentations and papers.

• This position requires strong analytical skills, working knowledge of molecular biology, biophysics, and statistics, as well as experience using tools for molecular simulation, visualization, and analysis.

• The successful candidate will be highly motivated to learn and be part of our ongoing work to pioneer our lab's work to apply molecular modeling to interpret human genetic variation's effects.

• Working experience with structural bioinformatics tools and algorithms is required (either by command line or IDEs).

• Experience with Linux-based HPC systems is preferred but not required.

• The successful candidate will receive training on the established workflow and modeling process, with opportunities to improve and expand the workflow, especially in the automation of machine learning and statistical mechanics approaches to evaluating protein structural and Molecular Dynamics data for their cellular and biological meaning.

• The priority for the current position is to apply our approach to chromatin regulatory complexes.

• The successful candidate will be organized, detail-oriented, demonstrate an ability to critically read, understand, and interpret scientific publications, and effectively communicate verbally and in writing.

Appropriate experience may be substituted for education on an equivalent basis.

Minimum Required Education: Bachelor's degree- Bioinformatics, Structural Biology, Molecular Genetics, Biophysics, Molecular Biology, Machine Learning/AI, or comparable field

Minimum Required Experience: 1+ year

Preferred Education: M.S. or PhD

Preferred Experience: 1+ year or Thesis, Dissertation, or Publications with direct relevance

Work requires occasionally lifting moderate weight materials, standing, or walking continuously.

Occasional exposure to dust, noise, temperature changes, or contact with water or other liquids. Work is performed in an environmentally controlled environment.

Ability to detect and translate speech or other communication required. May occasionally require the ability to distinguish colors and perceive relative distances between objects.

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