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or experience in strong collaborations and interdisciplinary work at the intersection between machine learning, geophysics and acoustic data modeling. A strong experience with software defined radio Automatic
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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description Conduct a literature review on SSMs, LLM architectures, and hardware acceleration techniques. Investigating design choices that optimize the model across both the hardware and software stack. Design
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of AI/ML will be an added advantage. Proficiency with optimization tools and software like GAMS, CPLEX Proficiency with programming languages preferably Python, Matlab Fluency in communication and
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Hardware-software co-simulation and benchmarking This PhD project is part of SDU microelectronic unit’s effort in neuromorphic chip design and collaborates with international partners working on spiking AI
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Development/upgrading solid oxide cell test setups for advanced electrochemical characterisation, including development of metal test houses Development of dedicated circuitry and analysis software
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Software Defined Vehicles (SDV). The primary objective is to expand, mature, and industrialize a novel European RISC-V automotive ecosystem that enables next-generation high-performance European automotive
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, secure digital communication, medical technology, and new analytical methods. We use and develop basic theory, next-generation instrumentation, and software, and aim to make our data publicly accessible
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, suitable for wearable or implantable devices. The research will focus on hardware-software co-design, from modeling spiking behavior to implementing scalable architectures on silicon. Key research themes