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They bring scientific talents in molecular biology, immunology, pharmacology, protein chemistry, computational biology, automation, genome engineering, software and other fields to make the future happen now.
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Existing collaborations within CZ Biohub: Technology Platforms (Bioengineering, Computational Microscopy, Data Science, Genomic Sequencing, Mass Spectrometry/Proteomics), and Research Group Leaders.
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Ph. D. in Statistics, Applied Mathematics, Biomedical/Chemical Engineering, Computer Science, Physics, Computational Biology, or related field. Family care services such as adoption and surrogacy reimbursement, fertility/infertility benefits, support for traveling mothers, and child, elder and pet care resources.
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Stay Abreast of Industry Trends: Keep abreast of emerging trends, technologies, and methodologies in cheminformatics and computational chemistry, and integrate relevant advancements into our drug discovery pipeline.
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Collaborate with multidisciplinary teams of virologists, cell biologists, computational microscopists, and genomics and proteomics experts. We actively collaborate with virology, cell biology, genomics, proteomics, microscopy, and data science teams across CZ Biohub San Francisco.
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Must successfully complete competency-based interview with a focus on high performance computing disciplines (such as CFD, FEA, Molecular Dynamics, Weather Forecasting, Computational Chemistry, Reservoir (Seismic) Simulation, Media Rendering, Machine Learning, Financial etc.
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The College connects the Data Science Undergraduate Studies program, Department of Electrical Engineering & Computer Sciences, Department of Statistics, the Berkeley Institute for Data Science, Computational Precision Heath, and the Center for Computational Biology.
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Experience with finite element analysis (FEA) and computational fluid dynamics (CFD) simulations. Experience with finite element analysis (FEA) and computational fluid dynamics (CFD) simulations.
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MINIMUM REQUIREMENTS: Must have a Bachelor’s degree in Economics, Quantitative Finance, Financial Engineering, Computational Finance, or a related field, plus 5 years of progressive, post-baccalaureate related work experience.
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PhD in computational biology, computer science, data science, physical science, statistics, or a related field with a minimum of 10+ years of relevant work experience. We have an exciting opportunity for a scientific leader with deep analytical and computational expertise in Research Data Sciences at Gilead.
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As a member of our computational neuroscience team, your primary responsibilities will be to design, implement, and improve algorithms to process surface electromyography (EMG) and other neural signals.
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The Krogan lab applies Systems Biology approaches such as proteomics and functional genomics, as well as biochemistry, computational biology, and bioinformatics to unravel the molecular networks underpinning neurodevelopmental/psychiatric and neurodegenerative diseases, as well as cancer and infectious diseases.
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Bachelors with 8+ years’ experience, Masters with 5+ years’ experience, PhD with 3+ years’ experience, or equivalent work experience in a field emphasizing applied organizational research and quantitative analysis (e.g., Industrial-Organizational Psychology, Applied/Behavioral Economics, Organizational Behavior, Business Management, Public Administration/Policy, Computational Mathematics, Computer Science.
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The central project will 1) apply cutting edge signal processing and computational neuroscience techniques to analyze data recorded from hundreds of locations directly in the brain, and 2) use brain stimulation to understand the mechanisms of memory function, and how epilepsy affects these functions.
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The company's platform combines the latest advancements in visualization of molecular interactions, computational chemistry, and data integration to design orally available, superior small molecule medicines that overcome current limitations of biologic and peptide drugs.
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computational job Title: senior fellow in South San Francisco, CA
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Talent acquisition is a multi-stage process where candidates undergo various application steps before getting hired. The unfortunate reality is that it is a labor-intense system, with the hiring manager and recruiter often handling all of the work on their own. Ask any one of them, and you will hear about the overabundance of applications and the demanding task of filtering through them to find the best candidates. The quality of talent suffers under the weight of all that work on one person's hands. It's not easy, but as many companies are starting to realize, there is a better way. The future of talent acquisition lies in collaborative recruiting!