Metagenomics Data Science Co-op

Location: 
Chesterfield, MO 06317
United States
Job Posted Date: 
August 11, 2022
Opportunities: 
Internship Positions
Population: 
Global Health
Life Sciences
Population & Social Sciences

YOUR TASKS AND RESPONSIBILITIES

 

The primary responsibilities of this role, Metagenomics Data Science Co-op, are to: 

 

  • Provide technical contributions in a fast-paced team environment to accelerate our efforts on building an analytics-driven product pipeline;
  • Develop sustainable, consumable, accurate and impactful reporting on model inputs, observed outputs, and key performance indicators;
  • Present compelling, validated stories, including peers and internal customers to communicate research findings;
  • Use advanced metagenomic assembly, annotation, and analysis methods;
  • Form partnerships with cross functional teams to drive novel metagenomics insights;
  • Leverage microbial, ecological and metagenomic knowledge and applied statistical or machine learning methods to deliver new insights to the pipeline.

 

WHO YOU ARE                                         

 

Your success will be driven by your demonstration of our LIFE values.  More specifically related to this position, Bayer seeks an incumbent who possesses the following:

 

Required Qualifications:

 

  • Currently enrolled in a Master’s degree or Ph.D. program;
  • Educational preparation or applied experience in at least one of the following areas, Machine learning, Biostatistics, Bioinformatics, Genomics, Computational Biology, Microbiology, Ecology or related quantitative discipline;
  • Knowledge of metagenomic methods and software;
  • Demonstrate basic computational skills and level of experience using R, Python or other statistical and/or mathematical programming packages;
  • Entry level proficiency in applied statistics;
  • Entry level proficiency in machine learning algorithms and concepts.

 

Preferred Qualifications:

 

  • Knowledge of next flow or other bioinformatics workflow languages;
  • Familiarity with cloud computing, high performance computing clusters;
  • Background in ecology, plant/soil science, agriculture.

 

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.  

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. Job postings will remain open for a minimum of ten business days and are subject to immediate closure thereafter without additional notice. IMPORTANT NOTE for POTENTIAL US CANDIDATES: Bayer expects its employees to be fully vaccinated against COVID-19. Bayer active employees are also expected to disclose their vaccination status and if fully vaccinated, provide proof of vaccination status to Occupational Medicine. 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 employees are also required to comply with state, local and customer requirements. Division:Crop Science  Reference Code672461 Functional Area:General Administration & Corporate Services  Location:United States : Missouri : ChesterfieldEmployment Type:Internship Position Grade:M00 Contact Us AddressTelephoneE-MailCreve Coeur, MO+1 888-473-1001, option #5[email protected]63167

Job Requirements: 
  • Currently enrolled in a Master’s degree or Ph.D. program;
  • Educational preparation or applied experience in at least one of the following areas, Machine learning, Biostatistics, Bioinformatics, Genomics, Computational Biology, Microbiology, Ecology or related quantitative discipline;
  • Knowledge of metagenomic methods and software;
  • Demonstrate basic computational skills and level of experience using R, Python or other statistical and/or mathematical programming packages;
  • Entry level proficiency in applied statistics;
  • Entry level proficiency in machine learning algorithms and concepts.
How to Apply: 

Must apply online at https://career.bayer.us/en?8f_query=672461&8f_location=USA&8f_pid=562949955655203&8f_domain=bayer.com&8f_hl=en&8f_triggerGoButton=false&8f_triggerGoButton=true&8f_job_description=false&8f__perms=&8f_host_url=https://career.bayer.us/en&8f_job_description=false

Location: 
National