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, Data Science, or a related field. Strong background in Natural Language Processing (NLP), Machine Learning, or Explainable AI (XAI); Experience with deep learning frameworks (e.g., PyTorch, TensorFlow
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, accelerometers, etc. - Proficient programming skills in Matlab/Python/LabVIEW, with an added advantage of specific experience in popular deep learning frameworks like PyTorch and TensorFlow. - Demonstrated
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(Assistant Professor in Evolutionary Biophysics) Prof Dr Marcos Guimaraes (Associate Professor in Optospintronics) Project description: How do insects see the world? And what can we learn from animal eyes
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see the world? And what can we learn from animal eyes to develop new sensors, such as smoke detectors, minute surgical cameras or autonomous vehicles? The animal kingdom offers a bewildering diversity
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deep learning research with a preference for ecological or environmental applications; Personal interest in ecology, marine biology, and/or environmental science is an advantage Strong programming skills
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that the tumors are not sharply defined and invade deep into the surrounding brain tissue. The challenge for drug-based therapy is that glioblastoma cells are very effective in developing resistance
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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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understanding of the success and failure of disruptive innovations. The potential scope of the project includes, but is not limited to, topics such as: The drivers and barriers of deep new technology adoption (in
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for candidates for a PhD in Computational Imaging for Cultural Heritage (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of the Leiden
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for Cultural Heritage (1.0 fte) As a PhD student, you will be embedded in the research group Computational Imaging and Deep Learning (CIDL), part of the Leiden Institute of Advanced Computer Science (LIACS). As