Data Scientist ML Genome Modeling

Key Skills

Aartificial intelligence, Deep Learning, Genomic data, Hierarchical Clustering, Machine learning techniques, Probabilistic Graphical Models, Probability

Job Description

Key Tasks:

• Develop state of the art AI assisted genetic discovery tools to uncover novel genetics with optimal phenotypic performance by leveraging advanced mathematical models and theoretically proven concepts of machine learning, Bayesian optimization, and/or graph theory;
• Train and analyze AI techniques on industry s most extensive global agriculture dataset (i.e. genetic and phenotypic data) in the world, including highly controlled and real world data;
• Develop models for assembling genomes of high throughput skim seq for tens of thousands of crop genotypes;
• Identify how complex genetic interactions lead to observed phenotypes in an efficient and interpretable manner and determine whether these insights lead to better design and predictions for our current and future intelligent pipelines;
• Assess feasibility and develop Artificial Intelligence/Machine Learning (AI/ML) for predicting phenotypes from high resolution genetic inputs, including raw reads/k mers to SNP markers in corn and soy;
• Investigate the efficacy of gene regulatory networks to establish an interpretable representation tool for realizing new trait experiments and gene editing targets in corn and soy;
• Be asked to lead or assist in several areas, such as: gather, curate, and quality control new data sources across Research and Development (R&D) teams;
• Implement Bayesian modeling frameworks on existing datasets/models and expand to more extensive data and improve Bayesian or AI/ML models;
• Work on a team as an individual contributor with other Data Scientists and builds cross functional relationships between Crop Science, Pharma, and Consumer Health divisions to collaboratively partner and effectively network within the Data Science Community;

Qualification & Competencies:

• Minimum of a Bachelor’s degree in: Machine/Deep Learning, Bayesian Statistics, Uncertainty Quantification, Computational Biology, Computer Science, Probability, Probabilistic modeling, Nonlinear Dynamics, Hierarchical models, Applied Mathematics, or other related quantitative discipline

YOUR APPLICATION

Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Science for a better life, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.

To all recruitment agencies: Bayer does not accept unsolicited third party resumes.

Bayer is an Equal Opportunity Employer/Disabled/Veterans

Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.

IMPORTANT NOTE for POTENTIAL US CANDIDATES: Bayer expects its colleagues to be fully vaccinated against COVID-19. Bayer defines fully vaccinated in alignment with CDC which is two weeks after completing the two-dose vaccine regimen or two weeks after completing the one-dose regimen. Additionally, Bayer colleagues are also required to comply with state, local and customer requirements.

Location:

United States : Missouri : Residence Based

Division:Crop Science

Reference Code:788586

Contact Us

Email:hrop_usa@bayer.com