9 deep-learning PhD positions at Delft University of Technology (TU Delft) in Netherlands
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research area. Prior experience working with Neural Radiance Fields or Gaussian Splatting. Prospective applicants should have a strong academic record with a solid background in Machine Learning (Deep
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strong academic record with a solid background in Machine Learning (Deep Learning, generative models, diffusion models). Knowledge in sensor data processing and radaris a plus. Good programming skills
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.). Experience with collecting and processing experimental data of human movement. A deep curiosity for how biological systems and structures function. Good written and oral communication skills in English. The
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, computational fluid mechanics, high-performance computing, and physics-informed machine learning. Affinity with physics-informed machine learning, computational VVUQ (verification, validation, and uncertainty
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stays, such as holidays, are not taken into account. Required Skills: Strong analytical background Proficiency in geometric deep learning, signal processing, statistics and learning theory The ability
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that promote positive collaboration among them. To achieve this, the PhD project will develop customized agent-based models using reinforcement learning. These models will help map out agent interactions and
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frameworks like RHEOS software, FEM models and machine learning concepts for large data sets generated will be explored with collaborators. Micro and Nano Engineering This position is embedded within
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Skills: High proficiency in Python programming languages. Ample experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and deep learning architectures. Knowledge of GNSS technologies and
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PhD Position Mechanosensing ion Channels in Artificial Lipid Bilayers Formed in Microfluidic Devices
, engineering, or a related field. Successful candidates are motivated by a deep scientific curiosity, have excellent experimental and quantitative skills and possess a drive to learn and to develop new methods