1,043 machine-learning-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL"-"UCL" Fellowship positions
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Innovations Group seeks a forward‑thinking expert in statistical machine learning to translate complex biological datasets into actionable AI‑driven insights. You will enhance genomic selection and breeding
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., • Interest in developing risk prediction models via deep learning/machine learning. • Have strong background in DL, EEG data and programming for the implementation of proposed methods. Apply now
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. Research Project: Joining a team of landscape and fire ecologists to learn about and support geospatial analysis of fire mitigation implementation in the highly fire prone lands of Kona and Kohala on Hawaii
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transformations. Combining automated reaction discovery simulations, microkinetic modelling, machine learning, and global optimization, this project will develop a new and exciting route to addressing one
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-machine teaming. Moreover, the consequences of such digital transformation are explored in the context of workforce and labor developments, organisational innovation, and learning/education. About the
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mapping tools such as Google Earth Engine or Microsoft Planetary Computer, and it is likely that developments such as satellite data embeddings and GeoAI will offer potential for increasing the accuracy and
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. Qualification requirements A PhD degree within neuroscience, psychology, medicine, machine learning or biology or equivalent. Doctoral dissertation must be submitted for evaluation by the closing date
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design and in silico validation intimately connected to experimental validation. In this project, you will develop machine learning methods and apply them in an interdisciplinary environment spanning
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Interaction, Interactive Computing, Product/Industrial Design or a related discipline and must have no more than five years of post-qualification experience at the time of application. Applicants
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and spectral index time series extracted you will work with solar physicist Mykola Gordovskyy (also at CAR) on initial physical modelling to better understand these extreme flares and to compare them