36 python-"https:"-"CIPMM---Systemic-Neurophysiology" PhD positions in United Kingdom
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- University of Birmingham
- University of Birmingham;
- University of Sheffield
- AALTO UNIVERSITY
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- Swansea University
- UNIVERSITY OF VIENNA
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- Abertay University
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
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visit: https://www.brunel.ac.uk/about/our-history/home We are seeking to appoint a Research Assistant who will work on the ELOQUENCE European project which aims to study Large Language models in
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conducting experiments, programming experimental tasks in platforms such as oTree, analysing experimental data using statistical and econometric software (e.g., Python, R, Stata), and reporting experimental
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Applicants with an interest in human
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, Computer Science, Neuroscience, Data Science, or a related field. An MSc degree in a relevant area is desirable though not necessary. Experience in coding (e.g., Python/R/Matlab) and experience in
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an allied field. An MSc degree in a relevant area is desirable though not necessary. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning
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employment policies. For further information on the WIRe scheme visit the web site at: https://cdtwire.com/ The project based at The University of Sheffield will be supervised by academics at Sheffield and
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in C++ and/or Python is expected, and experience in model analysis and parameter optimisation is beneficial. Experience in machine learning and neural networks is desirable. The successful applicant
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-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is desirable but learning can be completed during the PhD. Excellent
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analysis. • Hydrological and hydraulic simulation. • Machine learning, including unsupervised clustering and predictive modelling. • Working with large, complex, multi-source datasets using MATLAB, Python