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and Mathematical Sciences | NTU Singapore We are looking for a Research Fellow to study quantum materials via Machine Learning. The role will focus on develop Machine Learning technique to help DFT
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) Experience in genomics, single-cell data, or machine learning (preferred) Why this is exceptional Build next-generation AI models of the human genome Work with one of the richest longitudinal PD datasets
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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the use of modern machine‑learning methods within applied mathematics—particularly physics‑informed learning, anomaly detection, data‑driven modelling, and the construction of surrogate models grounded in
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 10 days ago
qualification PhD in fluid dynamics, physics, applied mathematics, computer science, or a related field. Experience with machine learning, numerical methods for PDEs, TensorFlow or PyTorch, and Python. Experience
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the foundations for this. The ideal candidate should hold a PhD in a relevant specialist subject or is about to submit, or should have equivalent experience. A background in machine learning applied in
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. Possessing a Master’s or PhD degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge of speech, audio, time-series or signal processing is required. Ability
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. Job Requirements: Competence in working with languages such as C along with Python-based coding and AI development. Have a degree in Computer Science/Computer Engineering. Possessing a Master’s or PhD
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candidate will have recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically
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intelligence, and multimodal learning. The main objective of this position is to develop novel generative AI methods for computer vision applications, with a particular focus on Diffusion Models and Vision