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The Associate Director of Machine Learning will lead a team of data scientists and machine learning engineers to develop, implement, and optimize machine learning models that support our drug discovery and development processes.
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A cornerstone of this roadmap is the acceleration of its data transformation and of the adoption of artificial intelligence (AI) and machine learning (ML) solutions. A cornerstone of this roadmap is the acceleration of its data organization and adoption of artificial intelligence (AI) and machine learning (ML) solutions, to accelerate R&D, manufacturing and commercial performance and bring better drugs and vaccines to patients faster, to improve health and save lives.
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Work across mechanical engineering, stem cell biology, and machine learning to develop systems for handling large-scale cell biology experiments. Strong hands-on experience with CNC machining, 3D printing, manual machining, laser cutting, and other fabrication techniques.
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Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
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Using advanced machine learning and state-of-the-art non-invasive robotics, the team aims to communicate with these majestic creatures. Our core tenets are educating broad-minded students; interdisciplinary research; integration across disciplines; and balancing theory, experimentation and practice to create an unmatched environment for learning and exploration.
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The ideal candidate will have a robust background in data science, machine learning, bioinformatics, and specific expertise in DNencoded library (DEL) machine learning and small molecule drug discovery.
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These may include, but are not limited to, predictive analytics, prescriptive analytics, natural language Processing (NLP), machine learning, generative AI, etc. Familiarity with data technologies such as data visualizations, Natural Language Processing (NLP), Machine Learning, generative AI. Comfort with big data approaches, such as data lakes, desirable.
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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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Emerging Technologies Group: Covers a wide range of work including Internet of Things (IoT) penetration testing, intelligent automation, artificial intelligence/machine learning and quantum computing.
$34 an hourFull-timeExpandApply NowActive JobUpdated 23 days ago - UpvoteDownvoteShare Job
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The Senior Lead Data will be responsible for partnering with Technology, Machine Learning, Product Architecture, and other Capital One teams to support the development of the Finance Tech Data Strategy into products and services we create and consume.
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Requirements: Currently pursuing a B.S., M.S., M.Eng., or Ph. D. in Biomedical Engineering, Electrical Engineering, Computer Science, or other relevant degree Python, MATLAB, and machine learning experience (coursework or practical) Preferred (not required): Biomedical signal/image processing (coursework or practical.
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Expected Qualifications: Demonstrated knowledge and teaching experience in at least one of the following areas: Statistics, Data Analytics, Data Visualization with different tools, Python, Data Management & SQL, Data Engineering, R Programming, and/or Machine Learning.
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Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data. This position is with the Signal Processing team at WHOOP. As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science.
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Collaboration: Collaborate closely with cross-functional teams, including bioinformatics, medicinal chemistry, biology, and machine learning, to integrate computational biology approaches into drug discovery projects.
$200,000 - $240,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Experience with data modeling, data prep and machine learning tools like Alteryx, RapidMinder, RStudio and Tableau Prep. Experience with statistical and mathematical modeling, artificial intelligence and machine learning software and methods.
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machine learning jobs Title: director Company: Fogpharma in Cambridge, MA
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