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for light trapping in thin-film solar cells .” You will become part of an enthusiastic team working closely with collaborators at DTU Physics and DTU Nanolab to advance neural network-based methods
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following areas: Probabilistic or Bayesian Machine Learning Variational Inference, Ensemble, or Diffusion Models Spatio-Temporal or Sequential Modelling Graph Neural Networks Deep Learning and Uncertainty
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Neural Networks Deep Learning and Uncertainty Quantification Python and ML frameworks (TensorFlow, PyTorch, JAX) Reproducible and open-science practices Experience with geospatial, environmental
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a postdoc in the field of Neural Speech and Audio Signal Processing as per December 1, 2025
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, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit-learn, PyTorch) or physics-informed neural networks for thermal systems is a plus
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-learn, PyTorch) or physics-informed neural networks for thermal systems is a plus. Excellent communication and collaboration skills across disciplines. We offer DTU is a leading technical university
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of complex microfluidic hydrogel networks, integration of micropumps for bubble-free aseptic perfusion, and non-contact mapping of multiple metabolites during tissue culture. You will be working on all aspects
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recognised track records. CNAP participates in numerous international initiatives and maintains an extensive global network, making it an ideal environment to build your own collaborative connections. CNAP is