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fractionation (i.e. surface biotinylating, gradient centrifugation, and be proficient in advanced data analysis (i.e. R, Python). Excellent analytical, organisational, and problem-solving skills are essential
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conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a related field together with strong programming skills in Python, R
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models for transport. Experience in using MATLAB/ Python/Siemens Simcentre to develop AI-assisted programme and models for powertrains and propulsion systems within the transportation and energy sectors
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operation · Application of artificial intelligence or machine learning in energy or engineering systems 5. Strong programming and modelling skills using relevant tools such as Python, MATLAB
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-centred AI, digital twins, or related areas 3. Excellent publication record in high-quality journals and/or conference proceedings 4. Excellent programming skills, particularly in Python and/or C
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; supervising student projects/practicals. · Demonstrable ability to model experiments using a range of software packages, such as Python, Matlab or Mathematica. · Experience of experimental
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theoretical understanding of statistical machine learning methods relevant to the project: Bayesian learning, machine learning, spiking neural networks. Experience of programming (e.g. with Python) and data
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for handling and analysing large and complex geophysical datasets, including programming skills in languages such as Python or Matlab. 10. Skills in description, analysis and dating of sediment cores. 11. Skills
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Python or Julia). Experience of computer-aided design (CAD) of components and devices. Experience of using and/or writing numerical simulation code. About Heriot-Watt University At Heriot-Watt we