51 - 200 employees
𧬠Biotechnology
π€ Artificial Intelligence
βοΈ Healthcare Insurance
π° Series C on 2022-10
October 29
51 - 200 employees
𧬠Biotechnology
π€ Artificial Intelligence
βοΈ Healthcare Insurance
π° Series C on 2022-10
β’ About Us: Valo Health aims to accelerate the drug discovery and development process. β’ About the Role: Join the computational biology core in the Translational Data Sciences group. β’ What youβll do: Integrate omics data, ensure data quality, perform analyses, and provide expertise. β’ What you bring: Educational background and experience in bioinformatics and computational biology.
β’ BS+4, MS or PhD + 1 years experience in bioinformatics, computational sciences, computational biology, or related fields (e.g., genetics, molecular biology) in collaborative settings to unravel complex biological data challenges and communicate domain knowledge to non-computational stakeholders & colleagues β’ Experience in modeling multi-omic (2 or more: genomic, transcriptomic, proteomic, and/or metabolomic) data with statistical/machine learning methods & biological network analyses towards understanding biological functions and disease processes β’ Experience with high-dimensional omics data and their challenges, including biological, experimental, and computational sources of noise & variance, and approaches to address multi-collinearity β’ Strong analytical, problem-solving, and communication skills, including facility with Rmarkdown and/or Jupyter Notebooks for communicating reproducible results β’ Ability to condense, summarize, and synthesize results into informative and actionable presentations to scientific audiences as demonstrated by original peer-reviewed publications in respected journals, oral presentations at scientific meetings. β’ Experience in R and/or Python, including familiarity with code, data, and model versioning β’ Experience with OMICs data processing workflows (e.g., nextflow, snakemake), evaluating QC metrics and adjusting for batch effects, and working in cloud environments (e.g., AWS) β’ Undergraduate or graduate level course work in at least two of the following: Cell Biology, Microbiology, Developmental Biology, Physiology, Immunology, Genetics, Epidemiology, Evolution, Biochemistry, Organic Chemistry, History of Science β’ Domain knowledge in cardiovascular disease and its co-morbidities (e.g., obesity, diabetes, and inflammation) preferred β’ Experience with network biology (eg, WGNCA) approaches to a plus β’ Familiarity with public data sources (eg, GEO, CMAP/LINCS, etc) a plus
Apply NowOctober 29
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