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Field
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commissioning, moving each station from operator-approved execution to full closed-loop operation, and test automation sequences in simulation with ARM's digital-twin team before running them on hardware. Publish
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from sensor data Design, integration, and validation of hardware-oriented demonstrators, measurement systems, and experimental test platforms Planning, execution, and evaluation of experiments
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materials and sensing technologies into robotics and other interdisciplinary research initiatives. Inline sensor system developmental work for 3D printing of non-newtonian materials. Optimization of hardware
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Supervise and mentor research associates, engineers, and PhD students working on the project Collaborate with perception, controls, systems, and hardware teams to guide integration of learned policies
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focus on simulation studies and may later involve hardware experiments with project partners. The role provides an opportunity to work with the PI’s team at the National University of Singapore, as
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on hardware and software co-design for systems targeting energy-efficient chips. The role involves developing, evaluating, and optimizing system-level techniques across hardware architecture, software stack
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Responsibilities: Set up and optimize local, open-source AI models (Stable Diffusion/ComfyUI) on high-end workstation hardware, with no cloud dependency. Train local LoRAs and ControlNets on a curated archive of the
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Max Planck Institute for Physics, Garching | Garching an der Alz, Bayern | Germany | about 1 month ago
Model. In parallel, the group is engaged in hardware activities related to the development and implementation of new FPGA-based trigger processors, both for the operation of the ATLAS muon spectrometer
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, build, calibration, and field validation of the environmental sensing payload and its supporting hardware sub-systems. This role is suited to candidates with a strong hardware, instrumentation, and
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. The position focuses on developing integrated circuits and hardware systems that merge sensing, signal processing, and inference directly at the analog and RF interface. This approach enables orders-of-magnitude