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Field
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an experimental apparatus aiming to develop a quantum processor based on Neutral Atom Arrays. The role will focus on developing the experiment, data acquisition and analysis, and supervision of undergraduate and
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for: Analysis of bulk and single cell RNA-sequencing, spatial transcriptomics, and proteomics datasets Integration of experimental model data with public and clinical datasets Statistical modeling and survival
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investigate computational complexity, stability, and numerical summaries of multiparameter persistence, as well as applications to medical image analysis, and participate actively in the research environment
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, machine learning, data-driven dynamics, stability/perturbation theory/rigorous numerics. Possible applications of the new theory include the analysis of spatiotemporal data arising from weather and climate
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi
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, and Large Language Modelling (LLM). Conduct extensive numerical experiments to validate and evaluate the performance of the proposed models. Present research results as academic papers and reports
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: Virgínia Isabel Monteiro Nabais Infante (ist13988) Organic Unit: Scientific Area of Mechanical Design and Engineering Materials Scholarship Theme: Experimental and numerical study of Mode I+III fatigue crack
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research teams. Responsibilities: Develop and apply AI-assisted weather and climate models with high spatial and temporal resolution. Integrate remote sensing, observational, and numerical model datasets
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reports. Job Requirements: PhD in Physics, Applied Physics, Plasma Physics, or related field. Demonstrated experience in scientific computing and numerical modelling (e.g., Python/C/C++/Fortran). Experience
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student mentoring Job Requirements: A PhD degree in Mathematics or related areas, with focus on numerical analysis or machine learning. Experience in computational math. Proficient in coding languages