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Take the computational biology lead on studies including; designing the study, the analysis plan and carrying out the statistical programming and data management to implement the plan. Ph. D. in Computational Biology, Biostatistics, Statistics, Bioinformatics or related field.
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The focus of this search is on faculty with substantial involvement in computational approaches, either in the area of computational chemistry/structural biology and/or in computational systems biology relevant to modern pharmacology.
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You will have deep technical savvy, a strategic mindset, and clear, forwarding-thinking leadership in AI/ML, computational biology and molecular biology, with a proven track record of leveraging computational tools to drive innovation in biotechnology, particularly in the realm of molecular biology, genome/transcriptome-wide analysis, single cell analytics, molecular design and structure, next generation sequencing, to predict RNA structure, regulation, and splicing.
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About the role The Computational Biologist will work closely with scientists and other computational biologists to analyze NGS genomics data and develop bioinformatics methods to solve exciting and challenging problems in cell and gene therapy, immunology, and stem cell biology.
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PhD in a relevant domain [Immunology, Computational Biology, Structural Biology, Bioengineering, Bioinformatics, or similar] with 3+ years of industry experience preferred. Senior Data Scientist, Computational Biology Department: DS/ML (Data Science/Machine Learning.
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Education Preferred: Master's Degree in Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.
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Master or Ph. D. in Bioinformatics, Computational Biology, Computer Science or related computational fields. Seeking a talented and highly motivated Bioinformatics Research Scientist to develop, optimize, and implement data analysis pipelines and analytical tools that enable comprehensive tumor genomic profiling for cancer biology research and cellular senescence biomarker discovery.
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Areas of research may include but are not limited to, the following topics: computational ecology and ecological modeling, especially around climate change, ecology of the urban/exurban/agricultural environments, interactions of ecosystems, and biogeochemistry with a focus on carbon sequestration and/or agriculture, ecosystem carbon accounting and fixation.
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A minimum of five years' experience in genomics and computational biology. The Kelley Laboratory in the Department of Ecology and Evolutionary Biology at the University of California, Santa Cruz (UCSC) invites applications for the position of Evolutionary Genomics Assistant Research Scientist.
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We apply a multidisciplinary approach to our research and actively collaborate with virology, cell biology, genomics, proteomics, microscopy, and data science teams at the CZ Biohub San Francisco.
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Design and execute protein engineering strategies to deliver developable biologicsformats by applying molecular biology, structure-guided, computational,combinatorial/display approaches. The Biologics group is responsible for various functions criticalfor drug development such as: antibody discovery, molecular biology, cell line engineering,protein engineering, biophysical analytics, and functional cell assays.
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In reality, this means working with the leaders of the following groups – AI Research, Engineering, Product, Computational Chemistry, Medicinal Chemistry, Biology, Business Development, and Operations – to ensure t.
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Masters degree or Ph. D. in a quantitative discipline such as statistics, biostatistics, computer science, bioinformatics, or computational biology. Position Description Calico is seeking an expert data scientist or computational biologist to join our multidisciplinary team of mass spectrometrists, biologists and computer scientists to become an integral part of our solution for proteomics.
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The department is focused on developing new areas of therapeutic engineering, pharmacogenomics, computational biology, systems pharmacology, drug development and regulatory sciences. A strong background in computational biology, image analysis, and a passion for advancing structural biology research are essential.
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We welcome candidates from all areas of computational genomics employing a spectrum of methodologies, spanning from computational biology to statistical genetics to machine learning and artificial intelligence.
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