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At Genentech Computational Sciences (gCS) Prescient Design, we are seeking a highly motivated Machine Learning Scientist to help drive research on Machine Learning for Drug Discovery.
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As a Principal AI Scientist, you are expected to: Lead advanced machine learning and analytical method application to extract disease biology insights and support innovative clinical development programs and publications on multimodal translational data sets that include single cell and spatial ‘omics, RNAseq, ctDNA, digital pathology, and clinical data.
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We want Data Science/Machine learning/Data Analyst and Java Full stack candidates. Currently, We are looking for entry-level software programmers, Java full-stack developers, Python/Java developers, Data analysts/ Data Scientists, and Machine Learning engineers for full-time positions with clients.
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6+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment. Work with clients to design, develop, and deploy new architectures for machine learning & automation applications such as ELT functions, HPC/compute infrastructure, hybrid cloud solutions, database management, and optimization of DevOps procedures.
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You have deep expertise building scalable data analytics and machine learning architectures and deploying them seamlessly in Cloud-native environments. You will work with a diverse group of engineers, data scientists, and risk modelers to evolve a platform and application suite that mesh data and machine learning to tame an expanding array of use cases, including automated underwriting, pricing, directed claims handling, and cyber - the #1 threat to US national security, above nuclear weapons.
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Collaborate to identify, evaluate, and recommend novel and cutting-edge automation and assay strategies to drive our discovery programs, including machine learning and artificial intelligence.
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Experience in applying Client analytical or computational (machine learning) technique and data science expertise to integrate and mine large complex data is a plus. Qualifications:· Candidates should have a doctoral degree in bioinformatics, computational biology, statistics, data science, other relevant fields with at least 1-3 years/ master’s degree with at least 5-7 years/BS degree with at least 10 years of relevant post-degree experience, preferably in pharma/biotech or related research organizations/academia.
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Experience with data analysis and visualization software platforms (e.g., Genedata Screener, Tibco Spotfire, GraphPad Prism, etc.) Scientist - Biochemistry & Pharmacology. The professional we seek is a motivated scientist with these qualifications.
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Ph. D. in Statistics, Applied Mathematics, Biomedical/Chemical Engineering, Computer Science, Physics, Computational Biology, or related field. Ideally the individual will also have interest in developing and deploying apps and tools for colleagues of various backgrounds as well as adapting approaches from machine learning.
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You Will Push forward on the state of the art of deep learning to solve extremely challenging real world robotics problems that is already driving at large scale. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers.
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Expertise in handling, analyzing and visualizing assay data sets and proficient in software platform such as GraphPad Prism. " A deep and broad understanding of the development, validation & execution of a wide array of binding & functional activity-based assays such as AlphaScreen, TR-FRET, FP, etc.
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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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Experience with cloud platforms such as AWS, Azure, or Google Cloud, and proficiency in using relevant tools and services for deep learning development and deployment. Requirements Key Responsibilities: Model Development: Design, implement, and optimize deep learning models for a wide range of applications, including image recognition, natural language processing, and autonomous systems.
$230,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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A graduate degree or equivalent in Machine Learning, Mathematics, Statistics, Physics, Economics, or a related technical field is preferred. Nice to have: Contributions to an open-source Machine Learning (ML) package, showing your skills in researching, implementing, and evaluating academic papers.
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Knowledge of analytics used to support purification development activities including HPLC, ELISA, SDS-PAGE and spectroscopy and proficiency to interpret data. As a Field Application Scientist at Ecolab , you will provide technical leadership by demonstrating application and theoretical knowledge of chromatography and downstream bioprocessing to design-in Purolite chromatography resins.
$150,000 a yearFull-timeExpandApply NowActive JobUpdated Today
machine learning data mining deep applied mathematics scientist jobs Company: Dice in South San Francisco, CA
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