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The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.
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Dana-Farber offers a variety of personal, professional, and leadership development opportunities to all members of its workforce through Division of Philanthropy offers 75+ specialized professional development sessions designed for staff each year through its in-house learning program, the Center for Advancement Training.
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Coordinate key research and development teams within BCS to ensure steady process of transfer of advanced technology research (artificial intelligence, machine learning, and other) into core product development roadmaps to support transformation to higher value “decision support” solutions.
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This candidate should have experience in at least one area of deep learning but have familiarity with a broad array of techniques, such as data pipeline development, metabolic engineering, or protein engineering.
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You will be responsible for designing, developing, and integrating core applications for CAD geometry preprocessing, including feature detection, slicing, layer generation, tile position generation, tile sequencing, engineering analysis, print process simulation, support generation, optimization and generative design for area printing, and machine learning / AI integration.
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Utilize programming languages like JavaScript, Node. JS, TypeScript, SQL, Python, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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Utilize programming languages like JavaScript, Java, HTML/CSS, TypeScript, SQL, Python, and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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The ideal candidate has a machine learning background, with previous experience building large-scale generative models, complex pre-processing pipelines, and comprehensive benchmarks to support scientific tasks.
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Should be competent with at least one numerically focused programming environment such as Python or Matlab using the native linear algebra, image processing, and machine learning libraries.
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Our core technical competencies include system-level modeling and gap analysis, advanced sensing and signal processing, machine learning and artificial intelligence, computational modeling, hardware and software prototyping, model-based systems engineering, and human data collection in laboratory and field environments.
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Responsible for one of the largest of the 56 Organ Procurement Organizations (OPOs) that make up the nation's donation system, NEDS works with over 200 hospitals and serves 14 million people in our region, screening nearly 55,000 potential donor referrals annually.
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Analytical Skill, Analytical Skill, Analytical Thinking, Chemical Biology, Chemistry, Clinical Trials, Collaboration, Communication Skills, Curiosity, Data, Data Analysis, Design Of Experiments, Detail-Oriented, Drug Development, Drug Discovery, Ethics, Gene Therapy, Immunology, Inventory Management, Laboratory, Lifesciences, Machine Learning (Ml), Management, Medical Research, Molecular Biology {+ 10 more.
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Understands, conducts, and documents appropriately Dialysis/Apheresis machine safety tests/alarm tests, equipment calibration, dialysate testing, machine safety tests, functional testing, and internal and external disinfection on all water & dialysis machines, and complies with the documentation/notification standards per FMS policies.
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6+ years of industry experience in drug R&D in pharma/biotech or life science-related industries with past experience involving both technical and strategic leadership High proficiency in developing and/or implementing AI/ML models in Python and R, particularly generative protein design, knowledge graphs and semantic modeling and inference, supervised/unsupervised learning, and LLMs. Experience with ML frameworks for deep learning (, tensorflow, keras, MXNet) & cloud platforms.
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Lead development and productionize cloud-based machine learning pipelines for small molecule discovery problems, including property prediction, target-ligand interaction prediction, and toxicology screening.
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machine learning open source one jobs Company: Simplyapply in Lexington, MA
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