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stakeholders in the Dutch battery ecosystem to develop and demonstrate the next-generation algorithms and models for the future Battery Management System. The PhD student will work on topics related to: Develop
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solutions, including training algorithms and preparing solutions for clinical implementation. Assess the impact of your workflow solutions after implementation, determining whether the expected improvements
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for problems that are 'quantum' NP-hard (QMA-hard). What you will do Quantum algorithms and complexity theory; Quantum error correction protocols; Quantum information theory; Classical representation of quantum
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participants of the Netherlands Twin Register, integrating genetic and psychological data where relevant. Beyond algorithm development, you will also address methodological challenges such as data quality, bias
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» Algorithms Mathematics » Computational mathematics Mathematics » Mathematical logic Researcher Profile First Stage Researcher (R1) Country Netherlands Application Deadline 16 Feb 2026 - 22:59 (UTC) Type
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learning and one PhD student with a keen interest in the algorithmic side of hyperbolic deep learning. Tasks and responsibilities: Conduct high-impact research on hyperbolic deep learning for computer vision
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or incomplete. Information Your tasks will include: Developing and benchmarking ML/AI algorithms tailored to low-data regimes — e.g. few-shot learning, transfer learning or data-efficient representation learning
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of hyperbolic deep learning and one PhD student with a keen interest in the algorithmic side of hyperbolic deep learning. Tasks and responsibilities: Conduct high-impact research on hyperbolic deep learning
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, enabling energy-efficient, quiet, and long-duration monitoring of ecosystems. The research will integrate novel lightweight perception modalities for robust perching in the wild, agile control algorithms
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systems strong analytical and problem-solving skills fluency in English, both written and spoken Not required, but helpful: Experience with biomedical data/algorithms An affinity for applications