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employment. Publication Track Record: At least two first-author research papers at flagship venues of core machine learning research (e.g., NeurIPS, ICML, ICLR, AISTATS). Theoretical Rigor: A deep
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topics: Development of deep learning models Mathematical foundations of machine learning Optimal deployment of AI systems The candidate is expected to hold a relevant MSc degree in Computer Science
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Science, Machine Learning, Artificial Intelligence, Computational Biology, or a closely related field Has strong theoretical and practical experience in deep learning Has hands-on experience developing
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degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis or unsupervised learning is an advantage
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efficiency. The goal is original research for leading machine-learning, computer-vision and robotics venues. The successful candidate will be expected to conduct original, high-quality research
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machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph representation learning. Programming skills (e.g., Python) and experience with deep learning
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, particularly ADHD, using large-scale genetic, imaging, and epidemiological data from Denmark and other countries. You will apply advanced analytical approaches, including deep learning and machine learning, to
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We are seeking a postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data