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Who you areYou will have a BS, MS, or PhD degree in the physical sciences (e.g. Chemistry, Physics, Chemical Engineering) or quantitative field (e.g. Computer Science, Statistics, Applied Mathematics) or equivalent industry research experience.
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Ph. D. in Statistics, Applied Mathematics, Biomedical/Chemical Engineering, Computer Science, Physics, Computational Biology, or related field. + Stay informed with emerging literature and science in the modeling and simulation sciences.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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What Additional Experience Makes A Strong Candidate: 4+ years of production experience with Scala 4+ years of production experience with Micro Services / Streaming Services Experience addressing ML problems, particularly in domains such as Time Series, Computer Vision (CV), Natural Language Processing (NLP), and data mining Proficiency with popular ML frameworks (Xgboost, TensorFlow, PyTorch, etc.
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Who You Are PhD degree in a relevant field computer science, computational biology, bioinformatics, molecular biology, cancer biology, genomics). The incumbent will apply advanced data analysis skills and machine learning in collaboration with a group of computational and biological scientists to perform translational oncology research around multimodal translational data sets for programs in clinical development.
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Significant experience in bioinformatics, applied mathematics and/or statistics to analyze multi-modal, multi-dimensional and large-scale biological datasets including whole exome sequencing, RNseq, and high-throughput proteomics data.
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Required Skills: PhD or MS in Bioinformatics, Mathematics, Statistics, Computer Science, or a related quantitative field. You will contribute to developing machine learning modeling and prediction pipelines using multi-modal biomarker data from clinical trials.
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PhD or MS degree in Applied Mathematics, Statistics, Engineering, or similar quantitative disciplines. You are a passionate, detail-oriented, and creative problem solver with a strong background in Data Science and Engineering, excited by the prospect of pursuing hard problems and exploring the unknown.
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6+ years of industry or academic experience in data science, economics, analytics, or machine learning engineering. 6+ years of experience using scripting languages (Python, R), and big data query/processing languages and tools such as SQL, Hive, Spark and Airflow.
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A minimum of 10+ years of related Industry experience as with a focus in sales, sales engineering, &/or technical product marketing, enablement, and/or enterprise software in data cloud, data warehouse, data engineering, &/or data science.
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Ph. D. in Bioinformatics, Computational Biology, Genetics/Genomics, Bioengineering, Computer Science, Biostatistics, or a related field. We are looking for a Head of Data Science to tackle complex computational questions within the gene-editing space.
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Experience in designing and building complex data processing systems at scale with performance tuning, and with with data processing frameworks (e.g. Spark, MapReduce, AWS EMR.
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Knowledge, Experience and Skills:Typically requires a BS/BA degree in Immunology, Microbiology, Molecular and Cell Biology or other related life science discipline and minimum of - years of relevant experience.
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Ability to process, analyze, and visualize data in R/Python (or similar) Department: Lab Science. MS or PhD in the biological sciences or engineering; familiarity with protein biochemistry/biophysics or protein engineering; strongly self-motivated individual with attention to detail; driven, team-oriented, and excited to work in a dynamic startup environment.
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In collaboration with a therapeutic area, the Scientific Director, Clinical Science will lead the design, conduct, analysis, and reporting of clinical trials. Contribute to creation of electronic database, IRT, and associated training documents and review data completeness and fidelity throughout study conduct.
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data science applied mathematics computer processing jobs Title: machine learning researcher in San Bruno, CA
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