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of the PostDoc project is to performreal-world testing of the shoulder device in healthy individuals and patients with upper limb movement disorders, as well as to develop the machine learning
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carriers within defects. The charge transport will be implemented stochastically to mimic nature. A significant focus of the project will be to apply machine learning techniques to optimize the model and
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this date. Job description Recent improvements in machine learning have dramatically improved the accessibility of de novo protein design. In this project, we seek to exploit these developments to interrogate
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which
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Natural Language Processing, Machine Learning, or a similar area. Expertise in large language model architectures and training paradigms (transformer models, fine-tuning strategies, RLHF, etc.). Interest in
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in combination with computational biology approaches to generate comprehensive models of gene regulation during development and diseases such as cancer and neurodevelopmental disorders. To learn more
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patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which
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the possibility of extension for three years. Tiwari lab employs cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation. In
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Postdoc position in Materials Characterization for Additive/Subtractive Manufacturing and Sustain...
approaches—combining additive (MIG welding-based) and subtractive (CNC machining) processes—for the refurbishment of industrial components. The postdoc will focus on characterizing material interfaces and
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background in modelling, optimization, and control approaches in energy systems, Research vision and potential Familiar with machine learning techniques Background in programming tools such as Python and Julia