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learning with a background in robust and embedded control, aerospace systems and physical modelling, as well as in artificial intelligence-related concepts, computer vision and numerical optimisation
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Posted on Tue, 03/04/2025 - 15:09 Important Info Deprecated / Faculty Sponsor (Last, First Name): Bohg, Jeannette Stanford Departments and Centers: Computer Science Postdoc Appointment Term: 2025
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the forefront of numerical analysis for Partial Differential Equations, enriched with data-driven methodologies -- a powerful combination that’s redefining what’s possible in computational science, and is playing
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MIMO communications Analog, digital and hybrid beamforming architectures Reconfigurable intelligent surfaces Machine learning for wireless communications Hardware-constrained signal processing
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. Develop advanced optimization, control, or machine learning strategies for distribution systems; validate these strategies using hardware-in-the-loop or real-time grid simulators. Develop optimization
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research scientist to work on the XENONnT Dark Matter experiment. About the Group: Led by Dr. Jingqiang Ye, our group is actively involved in both the hardware development and data analysis of the XENONnT
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Apply now Job no:525134 Work type:Post Doc (Amherst Only) Location:UMass Amherst Department: Elect & Computer Engineering Union: Post Doc Categories:Postdoctoral Research Associate, College
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Mathematics, Physics, Engineering, or Computer Science. This is a collaborative, cross-functional team, and project assignments will be tailored to match each postdoc’s strengths and growth goals. If you are
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, computational chemists, and neutron scattering experts. Major Duties/Responsibilities: Redox Flow Battery (RFB) Hardware Development: Lead the development and assembly of RFB hardware components. Perform informed
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optimization of optical imaging hardware, develop data acquisition software and algorithms for data processing, as well as perform phantom and human clinical studies. This candidate is expected to co-supervise