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Doctoral Candidate in computer vision and machine learning for developing novel deep learning method
funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Department of Mathematical Modeling and
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, by working at the intersection of engineering and economics to develop and apply energy system models to diverse energy systems and research questions. The Chair holder’s joint appointment as the Head
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the eDIAMOND project, namely: Distributing model training and inference over a network of resource-constrained devices. Online, context-aware adaptation of Federated Neural Network Architectures based
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, machine learning, and statistical modeling on cutting-edge datasets in precision feeding, animal behavior and welfare, multi-omics and environmental impact. Join our interdisciplinary team to drive real
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Researcher or experienced Data Scientist to harness AI, machine learning, and statistical modeling on cutting-edge datasets in precision feeding, animal behavior and welfare, multi-omics and environmental
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on studying shape parametrization, learning gait optimization functions for mechanism design and using different machine learning embeddings (such as GANS, VAEs, and Diffusion Models) for developing a new full
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setups with machining tools and employing additive manufacturing techniques (3D printing) Support and develop experiments, including feasibility checks and technical design with CAD tools and FEA (Finite
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by two ETH professors from two different departments. If you don’t have hosts yet, Design++ can help match you based on your proposal. Project background You are a great fit if you’re excited to: (a
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on our previous work on DNA tracing technologies, we aim to develop tools and procedures to model and monitor the spread of pathogens without directly employing and measuring pathogens. Project background
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and backtests to assess model performance and estimate the tool's real-world impact. You will have regular check-ins with the project team at Stanford but will conduct the day-to-day data work yourself