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Field
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responsible for: Conducting research on sustainable and resource-efficient AI systems for edge datacentres. Creating hardware-aware search spaces for CPUs, GPUs, and accelerators, and developing multi-objective
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) is required Desirable Qualifications: Experience with distributed temperature sensing (DTS) Experience with the use of heat as a hydrological tracer Experience with interacting with sensor hardware and
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related field; Strong knowledge of cybersecurity and cryptography applied to the automotive field; Knowledge of embedded systems and hardware features relevant to cybersecurity; Knowledge of communication
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addresses that challenge by developing a multimodal sensing and inference framework that can run on compact AI edge hardware while remaining reliable in complex, contested, or visually degraded environments
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hardware design: Verilog/SystemVerilog RTL, logic synthesis, and place-and-route Be familiar with Python programming Have a working proficiency in English. (Finnish language is not required.) The following
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(10%) 5. Skilled in modelling, simulation and programming (e.g. MATLAB, Python, ANSYS, Comsol etc.) (10%) 6. Skilled in Hardware in the Loop equipment (e.g. Opal-RT, Typhoon HIL, etc.) (10%) 7
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wall-clock time on available hardware. Thirdly, the quest of generality, namely the ability to simulate a variety of flows within a single software package has been a target in the development
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systems, optimization and networks, embedded and real-time systems hardware and software, fault diagnosis, cyber-security, reliability, resiliency and fault tolerance, cyber-physical systems, Internet
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that significantly improve occupant health, comfort, and overall well-being. Goals and Tasks The goal of the PhD project is to develop the hardware and software components of a smart acoustic sensing
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student will work in close partnership with researchers developing hardware interfaces for device data ingestion and will support clinical validation studies to evaluate the feasibility, acceptability, and