Graduate Scholar – Microbial Genomics
Bayer is a global enterprise with core competencies in the Life Science fields of health care and agriculture. Its products and services are designed to benefit people and improve their quality of life. At Bayer you have the opportunity to be part of a culture where we value the passion of our employees to innovate and give them the power to change. CS R&D BLX Informatics A Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and you have the “Passion to Innovate” and the “Power to Change”. 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. To all recruitment agencies: Bayer does not accept unsolicited third party resumes. The primary responsibilities of this role, as a Graduate Scholar – Microbial Genomics/Machine Learning, are to: Proactively identify and incorporate novel statistical methodologies to link bacterial taxonomy/genomics to function;Participate in a multi-disciplinary team of scientists who offer comparative genomics, pathway modeling, network analyses, and metagenomics for controlling pests and diseases in plant and promoting plant health using microbes;Conduct research and collaborate with scientists using machine learning methodologies to examine microbial processes and mechanisms that underlie plant-microbe interactions, produce secondary Metabolites, and contribute to primary microbial metabolism;Help drive the experimental design, analysis, and interpretation of HTS datasets incorporating total community analysis (functional gene analysis, phylogenetic and network analysis), comparative genomics, de novo assembly of targeted specific community, genes and selected microbial genomes;You will be joining a computational life sciences team which brings together expertise in biology, computational science, and statistics, bioinformatics, and software development;Be able to communicate effectively through listening, documentation, and presentation, especially using compelling visualization tools to share analysis and interpretation of data;Provide analysis and feedback about experimental results to supervisors, highlighting important results and defining next step experiments;Coordinate and cooperate on research activities with peers, supervisors, and subordinates;Communicate effectively by listening, documentation, and presentation. 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: PhD in Ecology and Evolution, Microbial Ecology, Microbial Genetics/Physiology/Ecology, Statistics, Applied Statistics, or Machine Learning (or nearing substantial completion, provided all Ph.D. requirements are successfully completed within 6 months of employment start date) OR M.S. in Ecology and Evolution, Bioinformatics, Microbial Ecology, Statistics, or Microbial Genetics/Physiology/Ecology, plus 1+ years of relevant experience;Proven ability to work within a reproducible framework, handling large data sets efficiently using scripts, databases, and other tools;Highly versed in experimental design methodologies, mixed linear modeling, and machine learning and be able to communicate the output with other scientists around interpretation of these statistical analyses;Knowledge of R or Python;Knowledge of other programming languages is a plus (UNIX, Perl, C, C++). Preferred: Knowledge of microbial physiology. Bayer is an Equal Opportunity Employer Minorities/Females/Protected Veterans/DisabledApply for this job.