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You have good knowledge and understanding of data science approaches including machine and deep learning; application in imaging domain (H&Es, IHC, radiomics) a plus.
$114,375 - $190,625 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Strong understanding of data science approaches including machine and deep learning; background in immunology, biology or oncology a plus. Demonstrated experience applying machine learning and deep learning algorithms to medical imaging analytics including CT, MR, and/or PET scans; experience in additional imaging domain (H&Es, IHC) a plus.
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Embed machine learning, artificial intelligence and GenAI capabilities into the cloud applications and solutions to enable predictive analytics, data mining, and pattern recognition for driving productivity and efficiency in solutions delivered.
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Learn more at Data Science and Digital Health Analytics & Insights team within Johnson & Johnson Innovative Medicine develops innovative solutions using a variety of data sources across multiple different disease areas, encompassing oncology, cardiovascular and metabolic disorders, immunology, neuroscience, and infectious disease.
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How you’ll make an impact: As a Staff ML Ops Engineer at SiriusXM, you will be a key player in our Data Platform Team. Your role will be pivotal in deploying, managing, and optimizing machine learning (ML) models, leveraging advanced tools like Databricks and MLFlow.
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S&P is a leader in risk management solutions leveraging automation and AI/ML. This role is a unique opportunity for hands-on ML scientists and NLP/Gen AI/ LLM scientists to grow into the next step in their career journey and apply her or his technical expertise in NLP, deep learning, GenAI, and LLMs to drive business value for multiple stakeholders while conducting cutting-edge applied research around LLMs, Gen AI, and related areas.
$150,000 - $215,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Deep understanding of data use cases in pharma/biopharma/healthcare including patient journey, performance management, targeting, market sizing & segmentation, customer affiliation, field alignment.
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Ph. D. in an engineering or science field such as Computer Science, Electrical Engineering, Statistics, or Applied Math Strong background in Deep Learning and/or Medical Image processing 4+ years of industry experience or post-doctoral studies in Computer Vision, Machine Learning and Image Understanding preferred.
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Knowledge of data analytics, machine learning, and AI applications in pharmaceutical manufacturing. Develop a deep understanding of the client’s workflows, APIs, Integrations and Cloud Databases and Data requirements.
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Applicants should have training and a significant track record in one or more of the following areas: -AI, deep learning methods-atmospheric, climate, and/or weather modeling-computer science, statistics, and/or machine learning with applications relevant to genomics-population genetics / genomics.
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Knowledge of other emerging technologies such as artificial intelligence, machine learning, or natural language processing in the context of content management. With a single vision as inspiring as “Transforming patients’ lives through science ”, every BMS employee plays an integral role in work that goes far beyond ordinary.
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Partner directly with CMG L&D team, IT research and technology as well as PCLs, Skill Developers and Skill Builders to implement emerging technologies throughout our workforce for the purpose of accelerating learning and development.
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Ability to independently research, interpret, analyze, and compile data, and present results. + Provide analytical and financial analysis support to the Budget Director and Chief Financial Officer, including responding to ad hoc data calls from DOE.
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ETS Research Institute is seeking a senior scholar with leadership experience in the intersection of digital learning, assessment and digital technologies such as artificial intelligence and process data to lead ETS’s emerging innovation research agenda.
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Familiarity and proficiency extracting external data from market research tools such as Bloomberg, AlphaSense, VisibleAlpha, FactSet, Capital IQ, and/or LSEG/Refinitiv. Our analyses incorporate various types of data & research (i.e., company publications, Investment Banking research, Industry Trade Publications, and financial data platforms) which is used to deliver key insights on the external market and provide in-depth analyses on our competitive position to senior leaders.
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