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and ML driven screening and optimization workflow to improve the generality of modern synthetic methods. Our first objective is to identify structural patterns and scaffolds that are accessible by
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++) for microcontrollers, as well as familiarity with automation tools (e.g., LabVIEW, PLC) and version control systems (e.g., Git). Additionally, they should showcase experience in prototyping, debugging, and testing
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of neuronal and vascular responses; Contribute to the instrumental optimization of the imaging system (detector configuration, illumination control, multi-camera synchronization); Analyze and interpret
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About the Opportunity JOB SUMMARY The Associate Vice President - Infrastructure leads several teams to ensure optimal performance, availability and scalability of Northeastern University’s IT
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& Modeling: Develop and simulate numerical models of damage and failure in aerospace structures, including FEA for metamaterials. Materials Design & Characterization: Study and optimize metamaterials and
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should be exclusively submitted through the consortium webpage https://raptor-consortium.com/recruitment/ RAPTORplus aims at adapting proton therapy treatment with multi-modality image information acquired
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University of Texas Health Science Center San Antonio | San Antonio, Texas | United States | about 3 hours ago
procedures, a clear chain of command, and a management structure responsive to the needs of both staff and patients. S/he will oversee the support of providers to ensure optimal revenue generation. The AACMO
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will work under the direction of Prof. Abhishek Halder and will conduct interdisciplinary research in the areas of stochastic control, optimal mass transport, and the Schrödinger bridge. They will pursue
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improved in several stages and continues to evolve. It will therefore be a question of carrying out the necessary technical upgrades and optimizing (fine-tuning) the different characterizations on reference
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monitoring and control. The research will design and evaluate hybrid AI + physics-based optimization frameworks that combine the accuracy and interpretability of physics-based optimization with the speed and