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Field
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objective of the project is to develop knowledge, models, and algorithms for physics‑informed autonomous control of heavy machinery in uneven and deformable terrain. Specific project tasks include fundamental
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predictive analytics Human factors, behavior science, and patient-centered design Advanced computing and scalable algorithms Decision science and learning health systems design Qualifications Required: Ph.D
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algorithms for the next generation of particle physics experiments and also explores other ways AI can accelerate scientific discovery. The group collaborates closely with computer scientists, astrophysicists
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learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms at the intersection of robot learning, control, and AI
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testing of model-free algorithms for real-time optimization of turbine operating conditions (e.g., yaw set points). Other projects may be assigned by the supervisor depending on skills and technical needs
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algorithms for mining molecular multi-omics and medical data to improve multiple tasks of precision medicine and discover new precision therapeutics. The successful candidates will work closely with our
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pipelines for large-scale scattering datasets. Participate in synchrotron experiments at APS beamlines to generate datasets that support algorithm development and validation. Work closely with ISAAC
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six sites in the city centre. The position We are looking for a postdoctoral researcher in molecular microbiology to investigate the genetic basis of drug tolerance in Mycobacterium abscessus , one
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will help design and build novel systems and algorithms that challenge traditional assumptions in databases, guided by both real-world needs and formal foundations. They will work at the intersection
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) and genetics data which are measured by longitudinally and cross-sectionally. • Developing and applying machine learning and AI approaches to identify interactive topological relationships