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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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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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capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives, including large-scale
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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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peer-reviewed publications Preferred Qualification Familiar with various chemical analyses and characterization instruments Experience in process modeling using Aspen or other software and TEA analysis
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), mouse models, fluorescence microscopy (confocal), genomics, epigenetics, cell biology and biochemistry techniques (e.g., RNA/ChIP-seq, mass spectrometry). Successful track record in conducting and driving
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language understanding, and more. Your work will directly influence our trading strategies and decision-making processes. This is a unique opportunity to work at the intersection of cutting-edge research and real-world
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 17 days ago
for highly-motivated and qualified candidates to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting
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contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models, alongside complex drug screening, efficacy
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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