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Field
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mouse models. Experience studying the hypothalamus or neural regulation of metabolism. Experience with neural tracing techniques. Experience performing stereotaxic surgery in mice. Excellent
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cell biological and biophysical characterization of various alpha-synuclein aggregates/oligomers found in vivo (Mouse models and human tissue) that can induce neuropathology/neurodegeneration. 1
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-particle physics, predictive modeling, and AI-enabled digital twins for magnetically confined fusion plasmas in tokamaks. The research will combine high-fidelity simulations, reduced transport modeling
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for model validation and material characterization Developing research proposals and leading individual research projects Analysing complex data and generating original research ideas Publishing in high
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advanced modelling and design of structural systems and materials, and you will contribute to strengthening the department’s activities in areas related to composite and sandwich structures and optimization
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learning models (e.g., multimodal AI, large language/world models) with specific finetuning for ELEVATE; designing geographically context-sensitive urban design recommendations that promote active mobility
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-based perturbations, base/prime editing, and targeted epigenetic modulation). Functional genomics in neuronal systems, including transcriptomic and epigenomic profiling. Model systems such as human iPSC
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, implementation of management treatments, and the use of coding and process-based models to analyze natural resource dynamics. Learning Objectives: Under the guidance of a mentor, you will build experience in plant
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) Investigate the role of key transcription factors in regulating hematopoiesis in conditional knockout and knockin mouse models. Candidates should have obtained a PhD or an MD/PhD degree and research training in
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, predictive modeling, machine learning, and causal inference methods. Experience with claims-based or EHR-based phenotyping, variable construction, treatment pattern analyses, healthcare utilization studies