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For methods builders we also welcome links to github/bitbucket pages, and relevant bioinformatics/computational biology/machine learning community contributions. PhD in a relevant subject area (Computational Biology, Population Genetics/Genomics, Bioinformatics, Biostatistics.
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Dr. Chen's research interests span a diverse range of fields, including control theory, network science, tensor algebra, numerical analysis, data science, machine learning, deep learning, hypergraph learning, data analysis, and computational biology.
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OR Master's Degree in biostatistics, bioinformatics, computer science, computational biology, epidemiology, or related field is preferred. Bachelor's Degree in Biostatistics, bioinformatics, computer science, computational biology, epidemiology, or related field with 2 years of relevant experience is required.
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PhD in Computational Biology, Biology or related field or bioinformatics preferred. Bioinformatician B: Master of Science in Computational Biology, Biology or related field or bioinformatics and 3 to 5 years of experience or equivalent combination of education and experience is required.
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BigHat Biosciences designs safer, more effective biologic therapies for patients using machine learning and synthetic biology. PhD in a relevant domain [Immunology, Computational Biology, Structural Biology, Bioengineering, Bioinformatics, or similar] with 3+ years of industry experience preferred.
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As an integral member of our Computational and Data Sciences (CDS) team, the candidate will work closely with the machine learning team to evaluate and assess new models that take advantage of our in-house database of binding affinity measurements and incorporate structural modeling and physics-based approaches.
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Stay updated on protein space and industry trends: Keep abreast of the latest developments in computational structural biology, protein engineering, and related fields. Strong familiarity with topics of protein and macromolecular structures and interactions with other proteinsExperience with cloud environments such as AWSExperience in developing machine learning platforms using modern ML frameworks for deep learning (, tensorflow, keras, MXNet) & deploying in services such as Amazon Sagemaker.
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The Sr. Research Investigator in Computational Biology and Data Science will provide advanced analytical, bioinformatics, and machine learning support for Translational and Discovery projects in Translational Medicine.
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The Principal Scientist, Computational Biology leads the development and deployment of computational methods for NGS-based clinical diagnostic assays in our clinical labs. Analyze large genomic and epigenomic datasets using cutting-edge computational biology methods to identify genomic alterations and biomarkers associated with cancer onset and progression and to craft novel tools to detect those patterns.
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You will have the opportunity to apply your knowledge in computational biology, machine learning, computer science, and statistics to develop and improve algorithms for analysis of multidimensional biomedical data and provide creative solutions to cutting-edge problems in genomics and drug discovery.
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Company: A cutting-edge biotech firm at the forefront of proteomics research is seeking a talented and experienced Director of Computational Biology to join their dynamic team in Boston, MA. This company is dedicated to advancing the understanding of complex biological systems and developing innovative solutions to address unmet medical needs.
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MD with clinical experience (e.g., residency), Ph. D., Masters or Bachelors degree in Medicine, Biotechnology, Statistics, Machine Learning & Artificial Intelligence, Physics, Mathematics, Computational Chemistry, Computational Biology, Biology or a related discipline.
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At least 10 years of industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in the area of natural language processing, human language understanding, computational linguistics.
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NSA Research Scientists are actively expanding the boundaries of what can be accomplished with artificial intelligence, machine learning, human-machine teaming, software reverse engineering, data science, novel architectures, cyber security, high performance computing, and computational linguistics.
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The Department of EEOB teaching portfolio includes shared undergraduate degrees in Biology, Genetics and Environmental Science, and shared graduate programs in Bioinformatics and Computational Biology, Ecology and Evolutionary Biology, Environmental Science, Genetics and Genomics, Interdisciplinary Graduate Studies, Plant Biology, and Sustainable Agriculture.
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machine learning computational biology jobs Title: research intern
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