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group has expertise in radiology, biostatistics and machine learning. We have a strong collaboration with research groups at KTH, at KI, and internationally within two EU projects and a new collaboration
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Machine Learning techniques to this data to extract the essential information contained within these trajectories. This will be achieved through the following steps: Develop tools to efficiently generate a
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Project title: Machine Learning models for subgrid scales in turbulent reacting flows Supervisory Team: Temistocle Grenga, Ed Richardson Project description: Supervised deep convolutional neural
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, develop methods to speed up this development by focusing on machine learning techniques to address sustainability challenges in chemistry research. We will explore novel pathways to process design and
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Positions: We have an opening for a PhD position in the areas of machine learning and computer vision. The position is supported financially by a SNSF project, whose aim is to build controllable
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machine-learning techniques in ST studies. Our approach introduces two innovations: developing sparse Bayesian learning algorithms for efficient small dataset analysis and designing a simulator for
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Join us in advancing the frontier of plant sciences and making a tangible impact on agricultural resilience through the power of machine learning! We are seeking a highly motivated PhD candidate
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, contains: Within the context of the Belgian funded EOS project “Photonic Ising machines” there is currently an open position at the Vrije Universiteit Brussel (VUB) for a PhD student in the field
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. Knowledge and experience in data science and machine learning is particularly beneficial. Excellent communication and interpersonal skills are essential, along with intellectual independence and a willingness
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an institution of higher learning and research with a deeply rooted interdisciplinary approach and a global perspective. SSM admits only the most promising graduate students through a competitive exam