Department of Statistics, 24-29 St Giles', Oxford
This post is fixed-term until 31 August 2024.
We invite applications for a part-time Research Assistant funded by the European Union, working in the group of Professor Yee Whye Teh at the University of Oxford. The post holder will be a member of Oxford Computational Statistics and Machine Learning (OxCSML) with responsibility for the provision of research support in the area of reliability of language models. The successful candidate will hold a relevant Bachelors or Masters degree in statistics, computer science, information engineering, or a commensurate technical discipline and be working towards a doctorate in machine learning. They should also possess sufficient specialist knowledge and interest in statistical machine learning, deep learning and large language models.
We proudly hold a Race Equality Charter Bronze Award and a departmental Athena SWAN Silver Award, which guide our progress towards advancing racial and gender equality. As part of our commitment to openness, inclusivity and transparency, we would particularly welcome applications from women and black and minority ethnic candidates, who are currently under-represented in positions of this type at Oxford. Applicants will be selected for interview purely based on their ability to satisfy the selection criteria as outlined in full in the job description. You will be required to upload a statement setting out how you meet the selection criteria, a curriculum vitae, and the contact details of two referees as part of your online application.
Please direct informal enquiries about the post to Professor Yee Whye Teh ([email protected]), quoting vacancy reference 170785.
Only applications received before 12.00 noon UK time on 19 February 2024 can be considered. Interviews are anticipated to be held on 23 February 2024.
Contact Person : Andrea Williams Vacancy ID : 170785 Contact Phone : Closing Date & Time : 19-Feb-2024 12:00 Pay Scale : STANDARD GRADE 6 Contact Email : [email protected] Salary (£) : £32,332 – 38,205 per annum pro rata