Computational Biology, Single Cell & Spatial Genomics Co-Op

Bayer CropScience Limited; Chesterfield (MO); On-site; USD 32,000 - 66,000; Part time

Benefits offered by this job

Health care

Vision

Dental

Retirement

PTO

Sick leave

Bonus/Commission

Job summary

Bayer CropScience Limited in Missouri is seeking a Computational Biology Co‑Op to support the analysis of single‑cell and spatial transcriptomics data. You will collaborate with computational biologists, geneticists, and genomics scientists to perform deep analyses and generate biological insights.

The role requires developing reproducible workflows, reviewing literature for new methods, and presenting results to multidisciplinary teams. A Master’s or Ph.D.

Qualifications

• Pursuing a Master’s or Ph.D. in Bioinformatics, Computational Biology, Genetics, Genomics, Data Science, CS, Statistics, or related field.
• Experience with biological data analysis using R and/or Python.
• Familiarity with transcriptomics or spatial biology data is preferred.

Responsibilities

• Analyze single-cell and spatial transcriptomics datasets using modern computational approaches.
• Perform in-depth exploration of existing datasets to identify biological insights and hypotheses.
• Conduct literature reviews to identify emerging analytical methods and findings.
• Create reproducible analysis workflows and document computational methods.
• Present findings and visualizations to multidisciplinary project teams.

Skills

R

Python

Data visualization

Problem solving

Education

Master’s or Ph.D. in Bioinformatics/Computational Biology or related field

Job description

Computational Biology, Single Cell & Spatial Genomics Co-Op

We are seeking a highly motivated Computational Biology Co‑Op to support the analysis of single‑cell and spatial transcriptomics datasets. The successful candidate will work with computational biologists, geneticists, and genomics scientists to perform deep‑dive analyses, evaluate emerging methods, and generate biological insights that inform future discovery and research efforts.

YOUR TASKS AND RESPONSIBILITIES

• Analyze single‑cell and spatial transcriptomics datasets using modern computational approaches;
• Perform in‑depth exploration of existing datasets to identify novel biological insights and hypotheses;
• Conduct literature reviews to identify emerging analytical methods and relevant biological findings;
• Create reproducible analysis workflows and document computational methods;
• Present findings, visualizations, and recommendations to multidisciplinary project teams.

WHO YOU ARE

Desired Qualifications

• Pursuing a Master’s or Ph.D. degree in Bioinformatics, Computational Biology, Genetics, Genomics, Data Science, Computer Science, Statistics, or a related field;
• Experience with biological data analysis using R and/or Python;
• Familiarity with transcriptomics, single‑cell sequencing, or spatial biology data is preferred;
• Knowledge of statistical modeling and data visualization techniques;
• Strong problem‑solving, communication, and organizational skills;
• Ability to work both independently and collaboratively in a multidisciplinary research environment.

Employees can expect to be paid a salary of approximately between $22.75 to $47.75. Additional compensation may include a bonus or commission (if relevant).

• bonus or commission (if relevant)
• health care
• vision
• dental
• retirement
• PTO
• sick leave

This posting will be available for application until at least March 19, 2027

Bayer offers a wide variety of competitive compensation and benefits programs.

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.

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Bayer is an E-Verify Employer.

Location: United States : Missouri : Chesterfield

Division: Crop Science

Reference Code: 883381

Contact Us

Email: [e-mail]