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Field
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cooperative, competitive, and mixed settings. Collaborative decision-making frameworks and decentralized learning algorithms. Adaptive, meta-learning, and context-aware strategies to enhance policy
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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interaction and analytics using AI. Key Responsibilities: Development of artificial intelligence (AI) technologies to perform human-robot interaction and analytics System integration of the developed algorithms
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- “Data-driven algorithms for multi-product inventory systems with non-stationary demand”. Qualifications Applicants should have:- (a) a doctoral degree, preferably in the area of operations management
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development team Interacting with Continental business areas Developing and integrating AI algorithms into the real development progress Preparing academic publications such as patent applications and research
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operation of the umFm module unit used in vertical farm which includes handling of soil compost, irrigating of the crops and taking note of the sensors incorporation in the vertical farm inhouse. Job
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to twelve months] Duties The appointees will assist the project leader in the research project - “Ultrasensitive optical microcavity sensor-integrated optofluidic biochips for early disease diagnosis
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-bioreactor systems for organ-on-a-chip applications. Integrate sensors, microfluidic control, and environmental regulation into compact bioreactor units. Collaborate with biologists and engineers to validate
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towards this goal. The PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing (https://www.hvl.no/en/research/phd
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the Fellowship Coordinator, Andrew Aldapa, Aaldapa@mednet.ucla.edu The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration