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Field
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Modelling post combustion amine CO2 capture plant School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof Mohamed Pourkashanian, Prof Lin Ma, Dr Kevin Hughes
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locomotion. Apply machine learning and machine vision algorithms to track body and limb movements. Use biomechanical modeling to analyze walking data and fit locomotion models. Operate a force sensor to
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for the research topic “Modelling the impacts of soil pollution on soil ecosystem services”. The topic is focused on ecosystem services, soil ecotoxicology, soil contamination, and ecological risk assessment. The
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is part of the newly funded Research Council of Finland project Redefining Inner Boundaries in Solar Wind Models (RIB-Wind), led by Dr. Stephan G. Heinemann. The preferred start date is October 2025
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. Applicant must have (or expect to obtain shortly) a Ph.D. in Biological Sciences or related field. Experience with Neuroimmunology and/or Immunology is highly preferred. Proficiency in mouse models of disease
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will generate a wide range of contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models
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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
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Crustal Deformation and (2) Coastal Processes. We seek colleagues who creatively use theoretical, computational, observational and/or experimental approaches to address fundamental problems and processes
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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on addressing the complexity of the device-software-application-data design space, enabling systematic and efficient exploration using modeling and simulation tools.## Key Responsibilities- Identify and