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in the CV; b) Background and vocation for the design and development of large language models based on deep learning and capable of multimodal processing - information available in the cv and
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in the Fontana lab at Harvard Medical School in Boston Massachusetts. The work of the Fontana lab is focused on developing and applying software for modeling combinatorial systems of molecular
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include modeling of bulk and single-cell transcriptomic profiles, integrative multi-omics analysis, and the fusion of molecular data with clinical and imaging features. Organizational Status The successful
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amplitude analysis and scattering theory, heavy-ion collisions and the properties of hot QCD matter, hadronic probes of beyond-the-Standard-Model physics, and formal developments in lattice QCD. A Ph.D. in
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the application of security mechanisms in LLMs. (ii) Survey of requirements and planning of mechanism(s) that provide security for model input and output data in the context of code generation. (iii) Implementation
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, design, implement, and validate an optimization system for scheduling group classes within the Koachy platform. The specific goals include: Develop attendance prediction models for different types
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an agricultural context, in order to complement existing public datasets, which have enabled the validation of the solutions developed and, eventually, the improvement of existing models. This fellowship also aims
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the WATOC Dirac Medal. As the successful candidate, you will contribute to the design and implementation of AI models that integrate quantum mechanical theory with deep learning, enabling rapid and
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or condensed matter physics, with a focus in materials modelling using density functional theory. The research projects of the postdoctoral research fellow are thematically linked to the The Finnish Quantum
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be placed on Representation Learning techniques, Transformer-based architectures, Large Language Models (LLMs), Natural Language Processing (NLP), etc. The research will also explore distributed data