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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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engineering and wave-wind theories is advantageous Experience in coding (e.g., Python) and in the use of Structural Analysis Software (e.g., OpenSees, Abaqus) is highly desirable Ability to work independently
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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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, 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