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Documenting and testing codes Improving upon existing machine learning and numerical models Your qualifications: Excellent Python programming skills, Matlab and C++ experience is a plus Interest in Space
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Context and Motivation Bilevel optimization problems, in which one optimization problem is nested within another, arise in a wide range of machine learning settings. Typical examples include
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Engineering, etc.), expertise in cutting-edge AI and machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role
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utilizes a widely available diffraction-limited spinning disc confocal microscope (although not limited to this modality) for imaging. A single-step, machine-learning based approach is then applied
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in, but not limited to, the following areas are especially welcome: Reinforcement Learning Virtual Reality, Augmented Reality, Digital Avatars Embodied AI Natural Language Processing Human-Computer
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an excellent scientific track record. Proven expertise in environmental genomics, metagenomics, or large-scale omics data analysis. Experience with machine learning or AI approaches in biological data is an
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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at the Assistant, Associate or Professor level. We are currently recruiting candidates with expertise in data science, machine learning, computational or systems biology, and/or bioinformatics, with interest in
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environment with a strong emphasis on curiosity driven research. We are a collaborative and interdisciplinary team and there is ample opportunity to learn new techniques and be involved in exciting science
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world-leading in the development of a specialised facility that will optimise organs for transplantation using machine perfusion to improve marginal organ utilisation and expand equitable access