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is desirable. Basic understanding of embedded systems and processor architectures. Strong programming skills (C/C++, Python; hardware description languages such as HLS or VHDL are an advantage
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of LLMs is desirable. Basic understanding of embedded systems. Familiarity with fault detection, system reliability, or troubleshooting techniques. Strong programming skills (C/C++, Python; hardware
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advance interoperability for single-cell and spatial omics across the scverse (Python) and Bioconductor (R) ecosystems. The project focuses on enhancing the FAIR capabilities of SpatialData , a modern
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sampling strategies in Python and C++ Apply your framework to analyse real biological datasets to demonstrate robustness, interpretability, and practical impact Contribute to open-source software tools
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experimental systems for cryogenic measurements Development of a microwave quantum control & readout stack Development of Python code to operate quantum systems Detailed experimental characterization
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the consortium Your Profile: Excellent Master and subsequent PhD in computer science, engineering, biophysics, applied mathematics, computational biology or a related field Proven programming expertise in Python
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reliability, or fault-mitigation techniques. Strong programming skills (C/C++, Python; hardware-description languages “e.g., HLS, VHDL” is a plus). Motivation to pursue a PhD and contribute to applied AI
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. or equivalent) in applied mathematics or in computational engineering science, computer science, simulation science with a strong background in applied mathematics Excellent programming skills (Python, C/C
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, electrical engineering or comparable A good knowledge of sensors, experimental setups and adjustment Programming knowledge in Python for evaluation and validation Experience in measurement technology in
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related field Strong background in numerical methods and machine learning Proficiency in at least one programming language (Python, Julia, C++, …) Good analytical skills Good organizational skills and