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plant genomics and AI. Computational ressources, including the GenomeDK high-performance computing cluster, with growing capabilities such as high-memory nodes and state-of-the-art GPUs
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within DNA and RNA sequencing, laboratory automation, CPU and GPU compute resources, proteomics, metabolomics, and advanced microscopy. The PhD candidate will be part of the ActiveSOIL team, linked
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of bioacoustic signals. Extensive experience with programming (Matlab, R, Python) including GPU programming is required, and familiarity with edge-based machine learning (particularly sound event detection), open
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Assistant Professor Position in Transient Electromagnetic Signal Processing, Modelling and Inversion
field data acquisition, processing, and interpretation. * Strong programming skills. Advanced Python programming is mandatory; experience with PyTorch, GPU-implementations, or other high-performance
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responsible for: Conducting research on sustainable and resource-efficient AI systems for edge datacentres. Creating hardware-aware search spaces for CPUs, GPUs, and accelerators, and developing multi-objective
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computational resources (with GPUs) A collaborative environment across research fields, including plant biology, quantitative genetics, and population genetics Opportunities for collaboration and research visits