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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, establishing measures of performance, and human data collection in laboratory and field environments.
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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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This position is a Senior Scientist, Machine Learning reporting to the AD of Machine Learning, in Computational Drug Discovery at Fog. We are seeking highly talented and motivated people to contribute to the development of the Computational Drug Discovery group, a strategic function in Data Science that is part of Fog's platform discovery engine for HeliconTM stapled-peptide drugs.
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2+ years of industry experience in supporting the development of production-ready solutions leveraging AI technologies: NLP, Deep Learning, Machine Learning. Graduate degree (MS or PhD) in Computer Science or relevant field with a focus on NLP or Machine Learning.
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The Adobe Document Cloud's AI & Innovation Team is looking for an experienced Senior ML Engineer to help with a variety of Machine Learning (ML) related projects. If you have a passion for shipping groundbreaking data-driven customer-facing features, learning new technologies every day, and working on high visibility projects with ample room for creativity, this might be a good fit for you.
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As a ML Platform Engineer on the Central Software (CSW) team, you will play an active role in implementing the tools, infrastructure, and pipelines that unify how our product and research teams get stuff done.
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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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Clarendon Center (12089), United States of America, Arlington, VirginiaSenior Machine Learning Engineer (Remote-Eligible)As a Capital One Machine Learning Engineer (MLE), you.
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Robotic Storage Technologies (RST) is building a team of engineers with Simulation and Machine Learning (ML) expertise as we transform Amazon's warehousing solutions through the power of Artificial Intelligence (AI.
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C10 Labs is looking to add a Machine Learning Engineer to our growing team. Deploy machine learning models into production environments, ensuring scalability, reliability, and efficiency.
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You’ll design, implement, apply, and operationalize machine learning solutions for complex tasks on large data sets, including extracting insights from multiple disparate data sources and types, such as cyber, language, and vision.
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Lead the design, development, and delivery of AI and Machine Learning solutions focused on NLP, ML and Robotic Process Automation, ensuring the adoption of cutting-edge techniques and technologies, using pertinent AWS, Google and other cloud technologies.
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Apply a variety of data science techniques to tackle customer challenges to include machine learning, generative AI, natural language processing, computer vision, reinforcement learning, statistical modeling, mathematical optimization, and data visualization.
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Applying next-gen technology, high-density storage and machine learning to solve today's complex distribution challenges, Symbotic enables companies to move goods with unmatched speed, agility, accuracy and efficiency.
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Develop and implement Machine Learning (AI/ML) models and algorithms in areas such as protein structure, quantum mechanics, and biomolecular (protein-protein and protein-ligand) interactions.
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