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Field
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hardware architects to establish how agentic AI and these languages co‑design with heterogeneous HPC systems (CPUs, GPUs, PIM, AI accelerators). Study performance and portability tradeoffs, leveraging
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, including calibrating hardware and software infrastructure for research, sensor data collection and analysis; validating and disseminating research protocols and tools; creating technology prototypes and
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under hardware constraints, beamforming techniques for FR3 and THz bands, reconfigurable intelligent surfaces (RIS), and integrated sensing and communications (ISAC). The research methodology will involve
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research on the design and development of next-generation wireless communication systems. Specific topics include, but are not limited to, waveform design for the THz spectrum under hardware constraints
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computing connected via a national quantum consortium called InstituteQ with many quantum-related activities. We also have access to real quantum hardware, including VTT’s Q50 and Helmi machines and Aalto’s
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, tape-out, and testing, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing. ● Emerging AI
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ligand libraries, bioinformatics analysis workflows, and hardware and software support. The incumbent works closely with the BSBC Director and interacts routinely with UNMC investigators and other
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selection and switching in real time Integrate surrogate models with physics-based solvers, e.g. SOFA, FEniCSx, SOniCS, and clinical or phantom data Deploy models on ARSPECTRA hardware, including optimisation
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simulating/implementing quantum algorithms for field theories on quantum hardware. Appointment Detail: This post‑doctoral position is a full‑time, 12‑month appointment with annual renewal contingent
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, tape-out, and testing, preferably with applications to AI systems ● Design, analysis, and modeling of AI hardware such as deep neural network accelerators or neuromorphic computing. ● Emerging AI