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are actively engaged in the development of innovative methods and algorithms to be integrated in a digital twin architecture for (de) manufacturing systems. You contribute to organizing and performing
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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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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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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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-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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-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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@kuleuven.beThe interviews are scheduled to take place on Tuesday, January 6, 2026. We kindly ask that you ensure your availability on this date. Add the following parts to your application in English (more
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for a maximum total duration of 4 years. Salary (scale 43) and conditions are in line with KU Leuven's pay scales and competitive by international standards. The appointment is scheduled to begin on