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this data. Clustering travel needs. To define different mobility needs and motivations based on the travel data, we apply different clustering algorithms (e.g., traditional k-means, density-based clustering
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Nation by being a member of or chairing committees (e.g., NAACCR). • Responsible for the design, implementation and maintenance of data integration methodology, algorithms and software which allows
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district heating networks, within the framework of the project "Data Analysis for Peak Load Stabilisation in District Heating Networks (DAS)". The work includes: design and implementation of RL algorithms
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to 3 different courses, with each section typically consisting of 22-28 students. Lecturers will be expected to provide high-quality teaching, student advisement, and learning support services, as
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provide insights into comparative physiology across different species. Of particular interest is the modeling of transport networks across multiple scales, including their function, development and
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, technical development, strategic planning, and attention to the long-term cultural impact of our field. Profile We are considering different profiles for this position. An ideal candidate is A: A research
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University of California San Francisco | San Francisco, California | United States | about 1 month ago
for applying proteomics and genetics data collected in situ for integrative structure modeling. Critical aspects of the research include: (1) Designing and executing methods to integrate data from different
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(tenured) in the following areas: Algorithms and complexity, Databases, High performance computing, Operating systems and Programming languages. The anticipated start date is August 8, 2026. These positions
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. The position emphasizes implementation and prototyping of systems that combine AI algorithms with IoT hardware and software. About KAUST Established in 2009, King Abdullah University of Science and Technology
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Networks (DAS)". The work includes: design and implementation of RL algorithms to address the challenges of peak load variations in district heating systems development and use of simulation models