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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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at the University of Michigan Medical School. Using a combination of in vitro and in vivo modeling, analyses of clinical brain tumors samples and multi-omics (including single cell and spatial transcriptomics) our
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 20 days ago
), financed by national funds through FCT Workplan: The main objective of the fellowship will be to study the effects of heterogeneity in spatially-structured or host-structured multi-species models governed by
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-imaging tumourigenesis within the optically translucent Drosophila pupa. 2: Establishing RNA sequencing protocols for implementation with a Drosophila tumour models (bulk, single-nucleus sequencing
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machine learning (ML) approaches offer a powerful framework for modeling complex catalytic materials with near ab initio accuracy while enabling simulations at significantly larger spatial and temporal
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, voids, delamination, corrosion, and internal structural discontinuities. The PhD candidate will investigate Vision Language Models (VLMs), Multi-modal AI solutions, and 3D scene reasoning approaches
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, and local communities. c. Architectural & Spatial Integration of the Yachting Industry Develop spatial models and layout concepts for: Shipbuilding and repair facilities Marina technical zones Yachting
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the Collaborative Doctoral Partnerships programme, training researchers at the science-policy interface. Where to apply Website https://jobs.unibas.ch/offene-stellen/phd-position-ai-driven-pathways-to-health
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the production of spatially granular and engineering driven representations of model results. Experience working across disciplines in multi-institution and multi-stakeholder collaborations is desirable