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discipline. Desirable Experience in machine learning, deep learning, data analysis, numerical modelling, or scientific programming (such as Python, MATLAB, or R) is desirable. Knowledge of hydrodynamic
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to experiment control and data analysis (Python, IMSwitch, PiScat) Ideally, you have experience working with DNA-origami and DNA-PAINT assays. You have an excellent command of written and spoken English What we
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at the bench or in analysis. Programming in Python, R or MATLAB, and any experience of analysing image or sequencing data. A previous research project, internship or Master's thesis in a related area. How to
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or Python). Knowledge of the social identity approach and health psychology models are essential, and experience of network science or computational modelling is desirable.
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quantitative and computational research. Good analytical and problem-solving skills. Experience or demonstrable potential in programming using Python, R, Julia, MATLAB, or a related language. The ability to work
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(e.g., Python, MATLAB, C++, etc). Strong written and verbal communication skills. Please contact the main supervisor, Dr Emily Manchester - [email protected] . Please send your CV and a
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of programming, computer vision, machine learning, or related discipline. Experience with Python and relevant AI/ML libraries (such as PyTorch, TensorFlow). Demonstrated knowledge of multimodal data processing
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discipline. Essential Good programming skills, preferably in Python/C#. Experience with machine learning, deep learning, or experimental AI evaluation. Interest in secure distributed AI, federated learning
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offer visa sponsorship for this role. Candidate requirements Essential Skills in programming, preferably in Python, and a suitable undergraduate / masters degree in the discipline of Computer Science, NLP
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expertise across all three. Good mathematical and analytical skills. Programming experience (such as Python, MATLAB, or similar) for simulation-based research, or be willing to develop this during the PhD