14 programming-"the"-"DAAD"-"IMPRS-ML"-"EURAXESS"-"O.P"-"Study-Group"-"ISCTE-IUL" positions at University of Reading
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: Head of Meal Plan Management Contact Email address: k.gray@reading.ac.uk We welcome applications from both external and internal candidates. As part of the University’s ongoing commitment to professional
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candidates who are invited to interview. We are looking for a candidate to join the new Agrifood Futures team and play a key role in supporting the implementation of this exciting programme of work. This role
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subject by the start date of the appointment Good programming skills (r, Fortran, Python) Familiarity with eco-evolutionary optimality approaches to modelling vegetation Experience with working with large
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dissertation supervision to students on our highly regarded undergraduate and postgraduate speech and language therapy programmes. We are currently ranked joint 1st speech and language therapy programme in
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cytometry. Our experimental programme is designed to interface and synergise with simultaneous theoretical developments of computational models and novel methods for analysing system purposes
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, as well as a range of external stakeholders Experience of managing projects in a research setting The ability to work as part of a team to progress a programme of work Good communication skills
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to plan and deliver some student training and stakeholder engagement activities, taking the lead on some events. You will: • Be highly organised with the ability to initiate work, balance competing
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to academic life; -Experience of pastoral role -A well developed 5 year research plan; -A willingness to play a significant role in the everyday life of the Law School. Please see the job description and
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-evolutionary optimality concepts and modelling Good programming skills Familiarity with relevant data sources for model evaluation Previous research experience and publication record The ability to use own
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Practical experience in using site and global data sets for model evaluation Good programming skills Familiarity with relevant data sources for model evaluation Previous research experience and publication