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Field
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-compliant data infrastructures that enable secure data sharing, reuse, and AI-driven analytics Exploring and implementing federated learning and privacy-preserving AI approaches for distributed clinical
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in the Urban Geographies (UG) programme group in the Geography, Planning and International Development department, which studies how resources, risks and political voice are distributed unevenly across
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, risks and political voice are distributed unevenly across urban spaces and populations, analyzing geographies of inequality. You will receive PhD-training through the Amsterdam Institute of Social Science
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of how genomic diversity is distributed in forest tree species, how it has evolved, and implications for the future. Methods range from: studying genomic characteristics that drive genome evolution
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developing a collection of spatially distributed models for these objectives within an encoder-decoder framework to reduce the dimensionality, enabling the use of multi-objective optimisation to generate a
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of non-model plant species like many forest trees. The McEvoy Lab draws from a variety of new approaches to develop a better understanding of how genomic diversity is distributed in forest tree species
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collaboratively. Desirable skills Experience in training or fine-tuning large-scale models (LLMs, VLMs) in distributed settings. Familiarity with cluster computing environments (e.g., SLURM) and Linux-based
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actively to take advantage of the qualities that diversity and an even gender distribution contribute to our operations. We have chosen media for this recruitment and therefore we reject contact with
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contract is based on § 2 WissZeitVG. Your Tasks: Generative diffusion models (DMs) learn to reverse a diffusion process from an analytically known prior distribution to a target distribution that is inferred
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of distribution channels, while craft breweries rely on agility, experimental product innovations, local stories and close work with the customer community. To achieve the goal, questionnaire surveys will be