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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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» 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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of battery modelling and algorithm development, with a strong emphasis on the data-driven modelling and control aspects. You will contribute to shaping the technologies that underpin a more sustainable and
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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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motivation, which includes your preference for performing theoretical and/or algorithmic research (max 1 page); a list of publications or prior projects (max 1 page); the names and email addresses of two
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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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experience (max 2 pages); a letter of motivation, which includes your preference for performing theoretical and/or algorithmic research (max 1 page); a list of publications or prior projects (max 1 page
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tagging algorithm development as well as physics data analysis, with a focus on Higgs boson physics, top quark physics, and searches for new physics signatures. This is what you will do After the discovery
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reference architecture for data visiting. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent