GRAD SCHOLAR – Microbial Genomics/Machine Learning To support R&D projects within Biologics Bayer CropScience (BCS), to drive innovative crop protection and plant health solutions, and to develop and implement b data analysis tools and algorithms. The candidate will work closely with wet lab scientists and computational scientists in West Sacramento, CA and other scientists throughout BCS.
Position: Major Tasks • Proactively identifying and incorporating 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 bringstogether expertise in biology, computational science, 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. Position: Skills • PhD in Ecology and Evolution, Microbial Ecology, Microbial Genetics/Physiology/Ecology, Statistics, Applied Statistics, Machine Learning (or nearing substantial completion, provided all Ph.D. requirements are successfully completed within 6 months of employment start date). • M.S. in Ecology and Evolution, Bioinformatics, Microbial Ecology, Statistics, 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; • Should be 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 is essential. • Knowledge of other programming languages is a plus (Unix, Perl, C, C++) • Knowledge of microbial physiology an asset _________________________ Bayer: Science For A Better Life Bayer Corporation BCOR-USHR-HRRS 100 Bayer Road Building 14 Pittsburgh, PA 15205-9741, USA Tel: 412-777-2906 E-mail: janette.gardi...@bayer.com Web: www.bayer.com