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. Computational chemistry will be used to create a library of model compounds differing in lipophilicity and to calculate their key physicochemical properties (e.g. melting point, solubility, size, chemical
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theory and framework to study and explain how different reservoir systems work and how to design them for specific tasks. The project will combine: Mathematical modelling of dynamical systems
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programming in Python, MATLAB, or C/C++; Experience with detection, classification, and geolocation of RF emitters, with demonstrated application to uncrewed aircraft systems (UAS), ISM-band devices, or similar
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applying different multivariate calibration strategies and machine learning approaches. Finally, the variation of the sensor measurements will be studied in relation to the cow’s health and combined with
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, international students and EU students without Settled Status will need to cover the difference between the home rate and the international. Visas and associated costs are not covered. Closing date: 20th April
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*ideal candidate* is expected to have: - Very good experience in programming in Python or Matlab and data analysis (essential) - Research experience (essential, e.g., through research MPhil/Master’s degree
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solar deployment and contribute to the future co location of solar and wind arrays. The studentship offers full training in experimental methods, data analysis (MATLAB), CFD, offshore renewable energy
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electricity risk indices for Europe and test whether firms more exposed to electricity price risk face different market valuations and stock return dynamics. Subject areas: Econometrics, Finance, Mathematical
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MATHEMATICA, MATLAB and/or C++ Eligibility requirements Applicants must not already hold a doctoral degree. Applicants must comply with the MSCA mobility rule: they must not have resided or carried out
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capable of stereotaxic surgery and handling delicate recording probes. They should be strongly self-motivated, ambitious, and able to use Python and/or MATLAB to analyze neural and behavioral datasets