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response, from which the fundamental operating wavelength can be deduced. Algorithmic extraction of those features is common practice, but very often suffers from hitting edge cases where manual parameter
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methods, Machine Learning algorithms, and prototypical Energy Management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a
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of research and innovation! Be part of change Software development of the DSP toolbox for LiFi system Implementation of algorithms and software development using C++, Python or MATLAB Technical documentation
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. Because of the specific structure of the inference problems occurring in metabolic models, direct application of these MCMC algorithms is, however, not possible. In this project, you will bring MCMC methods
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theory, ideally with a focus on mathematical approaches to quantum information theory, quantum algorithms or quantum complexity theory, or alternatively on other aspects of quantum information in
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efficient algorithms for large-scale stochastic systems Integrating data-driven methods for model estimation, learning, and validation Collaborating with interdisciplinary partners in healthcare and data
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following areas: Strong foundation in machine learning, optimization, and deep learning algorithms, including Transformer architectures. Hands-on experience or solid theoretical knowledge of LLMs/SLMs
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advanced mathematical algorithms and AI frameworks for modeling and optimizing power electronic components and systems. To support our team, we are looking for a working student (all genders) in the field
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-critial vibrations from sensor data, enabling data-driven optimization of machining processes. You will also implemet ML algorithms for additional use cases, acceleration workflows and enhancing
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mechanisms, optimisation algorithms and renewable energy systems WORK-LIFE BALANCE: Optimal conditions for balancing work and private life, as well as a family-friendly company policy. The option for flexible