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-scaled CMOS models. Advanced algorithms and architectures need investigation of power-consumption trade-offs. For instance, digital predistortion (DPD) can enhance power amplifier efficiency but
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at the KU Leuven, within the Biomed lab (https://biomed-kuleuven.web.app/research ) to develop new trustworthy AI algorithms for fracture detection based on novel photon counting CT technology. Particularly
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engineering or mathematical engineering Good understanding of statistics and machine/deep learning algorithms Interest in Biomedical data science Excellent programming skills in Python Proficient English, both
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constraints across the FR3 band. You will propose novel transceiver architectures and communication algorithms offering flexibility and the best power-performance trade-offs. You will also investigate how
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to express complex domain knowledge in a formal yet flexible manner, and (2) design AI approaches such as learning algorithms and reasoning engines that can exploit the provided knowledge? The successful
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-constrained platforms, without heavily relying on human interventions for hardware-aware optimization, or are unable to generate runtime-adaptive workloads, such as AI algorithms that evolve over time in
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technology development role, not a PhD or postdoc position. You will be part scientific staff, focused on building and validating devices, not publishing papers. Expect a dynamic mix of hardware development
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management and markets You will have the opportunity to conduct doctoral research in the field of energy management at the distribution level You will actively participate in PR and recruitment activities