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regarded as a strong advantage. Familiarity with bioinformatics tools and programming in R or Python is not mandatory but would be considered a valuable asset. Additional Information Benefits Terms
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, and validated outputs to strengthen the competitiveness of the Dutch high-tech sector. The PhD Candidate Position You will be supervised by Prof. Dr. Suzan Verberne and Dr. Niki van Stein at the Leiden
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of models, code, and validated outputs to strengthen the competitiveness of the Dutch high-tech sector. The PhD Candidate Position You will be supervised by Prof. Dr. Suzan Verberne and Dr. Niki van Stein
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machine learning. Strong proficiency with R/Python and machine learning frameworks (e.g., PyTorch, TensorFlow). Prior experience with workflow management tools (e.g., Snakemake, Nextflow). Familiarity with
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collaboration with a number of partners in both science and industry. The specific focus of the research done is to be determined in collaboration with the co-supervisors: prof. Rob V. van Nieuwpoort (Leiden
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will be co-supervised by Dr Christoph Leitner and Prof Luca Benini in the Digital Circuits and Systems Group at the Integrated Systems Laboratory (D-ITET, ETH Zurich). Project background This position is
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applicants typically have backgrounds in computer science, statistics or econometrics but should have an intrinsic interest for marketing problems. The PhD will be supervised by Prof. Dr. Lemmens and funded by
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analytical skills, including signal processing, statistical learning, optimization, deep learning, or information theory; Experience in programming, e.g., in C++, Python or Matlab. Qualification requirements
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care and treatment. Therefore, this project will be carried out partly at Maastricht University and partly at Epilepsy Center Kempenhaeghe in Heeze. You will be working closely with Prof. Dr. Teresa
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Kempenhaeghe in Heeze. You will be working closely with Prof. Dr. Teresa Schuhmann, Dr. Debby Klooster and Dr. Ilse van Straaten. We value open-minded collaboration, scientific rigor, and strong mentorship