437 algorithm-development-"Multiple"-"Prof"-"Prof"-"Embry-Riddle-Aeronautical-University" positions
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Field
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purposes to meet multiple information and strategic requirements for the various stakeholders of the university. The successful candidate will join a team of other data analysts and data scientists to engage
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(EHR) data built by a multidisciplinary team of software developers, machine learning engineers, clinical researchers and health informaticians. The CogStack team is at the forefront of building
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development, human-computer interaction, data analytics, user experience design, remote monitoring systems, energy optimization algorithms, and environmental impact modeling. Human-centric AI-driven sanitation
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Post Doctoral Fellowship: Development of a 'Battery Management System' for Lithium-Ion Batteries (11834) About UM6P : Mohammed VI Polytechnic University is an institution dedicated to research and
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, including GPUs embedded within NHS infrastructure. - Development and deployment of ML operations software and tooling for ML / LLM algorithms working over free-text clinical data and potentially mixed
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of Excellence for Data-Driven Discovery, applying advanced computational techniques to develop novel therapeutics. This position will work closely with researchers in the Center of Excellence for Data Driven
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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storytelling skills to produce videos that resonate with diverse audiences across multiple platforms. He/She will need to work closely with different stakeholders across NBS to achieve the intended impact for
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software projects, including defining roadmaps, managing implementation of new features, and coordinating multiple developers. Experience working in an academic research environment, particularly quantum
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input needs, accompanied by a boost in algorithmic development, e.g., multi-modal learning, transfer learning, federate learning, and knowledge embedding, etc. However, a significant motivation of