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PhD in Chemistry, Artificial Intelligence, Machine Learning, Data Science, Material Science, or a closely related field. Employ advanced AI and machine learning models, including deep learning and predictive analytics, to identify novel materials and predict their performance within battery systems.
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PhD or equivalent level degree in computer science, computer engineering or related field involving artificial intelligence, human behavior modeling, natural language processing, machine learning, multi-agent systems, deep learning, agent-based social simulation, data analytics, intelligent user interfaces, complex adaptive systems, decision support systems, learning technologies, augmented reality, virtual reality, simulation, robotics, data fusion, and/or game development.
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Our mission is to accelerate the transition to sustainable energy by leveraging the power of artificial intelligence and material science. Proficiency in Python, TensorFlow, PyTorch, and relevant computational chemistry tools.
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Cytokinetics is dedicated to advancing the frontiers of technology through the strategic application of artificial intelligence, machine learning, image analysis, and computational biology and chemistry.
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The role requires proficiency in patent prosecution, with a preference for expertise in electrical engineering, software-related technologies, data science/AI, networking technologies (especially network security), machine learning/artificial intelligence, and hardware security.
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You will be responsible for developing, improving and experimenting with methodologies and algorithms to support these efforts, using machine learning, deep learning, artificial intelligence and natural language processing techniques.
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Responsible to advance NOAA’s use in digital transformation Artificial Intelligence (AI) and Machine Learning (ML) techniques, working with the enterprise stakeholders as they tackle data management, integration, dissemination, warehousing, and governance to manage the complexity of critical mission data for actionable insights and decision making.
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In depth understanding of Machine Learning / Deep Learning / NLP concepts. Stay updated with the latest industry trends in AI and machine learning, and continuously look for opportunities to apply these advancements to improve the LLM infrastructure.
$144,000 - $270,250 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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Roles and Responsibilities: Conducting cutting-edge research in the fields of artificial intelligence, machine learning, and robotics, specifically as they relate to autonomous vehicle technology.
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The Specialized Products & Advanced Research Capabilities (SPARC) Group is seeking a Principal Machine Learning Researcher to be part of a multidisciplinary team of researchers and engineers dedicated to developing cutting-edge technologies with significant and immediate impact on our national security.
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As an AI Machine Learning Engineer, the individual in this role typically works full-time, focusing on designing and developing scalable solutions using AI tools and machine learning models.
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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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Job Title: Chemist with AI Expertise (Scientist/Senior Scientist) We cover 80% of the employee’s premium medical insurance cost through Blue Cross Blue Shield, dental insurance through Bento Dental, offer a flexible Paid Time Off program, and maintain a firm Harassment Policy that includes Diversity, Inclusion, Equity, & Gender Protections.
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The scholar will join a machine learning group with unparalleled direct access to clinical resources, as well as Stanford’s world experts in artificial intelligence, biology, and medicine.
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3-5 years of experience building and implementing artificial intelligence, neural networks, deep learning, or machine learning capabilities in software applications in a national security or academic environment.
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