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and algorithms for event-based fusion of two physically-colocalized event-based and depth vision sensors, simulate and analyse these models, and explore possibilities to realize them in CMOS ASICs
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, which performs basic and applied research on Internet technologies and distributed intelligence. IDLab possesses a unique research infrastructure, encompassing a wireless network testbed in the city and
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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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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and engineer novel optical designs. You have proven experience with programming and a motivated interest in programming image analysis algorithms. You have proven experience, or show a motivated
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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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analysis: Applying geospatial methods (GIS mapping, geographically weighted regression, spatial clustering) and temporal approaches (time-series analysis, distributed lag models, case-crossover designs
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AI through several shared Chairs across faculties (a Chair on the algorithmic and statistical foundations required to understand AI and its biases, and on today’s various applications of AI [Faculties
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generative AI algorithms and translate them into intuitive explanations. Interest in cyber-physical systems (CPS) and eco-cognition modeling. Good understanding of mathematical optimization techniques
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or PyTorch. Interest in explainable AI and contributing to explainability repositories for trustworthy, auditable algorithms. Experience or interest in cyber-physical systems (CPS), eco-cognition, and