Bayer is looking to solve the problem of predicting gene expression patterns using machine learning and statistical modeling to test gene expression predictions via high throughput molecular biology experiments
Requirements
- Experience with large sequence dataset analysis, statistics, Python/R;
- Experience working in a UNIX environment;
- Experience with machine learning;
- Derive key insights from recent scientific literature and apply to new datasets;
- Ability to design, plan and execute experiments, analyze data, and interpret results;
- Detail oriented and able to work independently and collaboratively;
- Excellent ability to clearly present data and results to a broad audience;
Responsibilities
- Collaborate with lead scientists to execute, analyze, and interpret high throughput molecular biology experiments to test gene expression predictions via machine learning and/or statistical modeling;
- Document research plan, methods, results and data analysis;
- Prepare and communicate reports and summaries in written and/or verbal form to key stakeholders and broad audiences across department group;
- Collaborate on preparation of sequencing libraries;
- Use machine learning and/or statistical modeling to predict gene expression patterns based on genome-wide datasets from diverse germplasm;
- Deliver analysis at scale in cloud computing environments;
- Follow established operational standards including best practices, safety protocols and compliance policies;
Other
- Enrolled within a university in the US, pursuing a MS or PhD degree in Biology, Molecular Biology, Biotechnology, Bioinformatics, or related field;
- Excellent written and verbal communication skills;
- Passion and creativity for solving problems;
- Ability to expand knowledge base through continuous learning;
- Prioritize and coordinate work within a larger team and across functional groups;
