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Field
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networks, online analysis with delay, and theory of distributed algorithms. Job description In our group, we try to apply and unite the approaches and techniques of theory and practice. Some members of our
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energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity
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Centre for Advanced Robotics Technology Innovation (CARTIN) is looking for a candidate to join them as a Research Fellow. Key Responsibilities: Develop novel algorithms for multi-agent inverse
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algorithms and parallel/distributed variational algorithms in AI/ML for application workflows and large-scale HPC and QC systems Develop quantum machine learning (QML) algorithms for optimization of multi
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processing algorithms from concept to implementation. Eligibility to obtain a United States SECRET clearance (or higher) is required for ongoing employment in this position Minimum Qualifications: 1
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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according to scheduling algorithms, patients' medical history and established clinical and facility standards. Coordinate both procedures and ancillary visits within a specific period established for each
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Health. Complex Procedure Scheduling Duties Determine if ancillary appointments (pre-procedure clinic evaluations, pre-anesthesia testing appointments, etc.) are needed according to scheduling algorithms
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trustworthy medical AI? Deep models already outperform humans on many benchmarks, yet in the clinic they remain black boxes: radiologists cannot see why an algorithm flags a lesion, and AI engineers cannot tell
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as