|Salary:||£34,314 per annum|
|Placed On:||24th May 2023|
|Closes:||27th June 2023|
Applications are invited for a research post related to the development of statistical techniques for prediction and prediction accuracy assessment in high dimensional environments. The post is part of a research project funded by the ESRC and led by Professor Jean-Yves Pitarakis (PI).
The post-holder will be mainly responsible for developing the code associated with the statistical estimation and inference techniques relevant to the project across multiple packages (e.g., Matlab, R, Stata, Python). Depending on research interests and background, the post-holder will also have the opportunity to be directly involved in research reporting and collaboration.
The successful candidate must be working towards or have recently completed a PhD in a quantitative subject and have a strong programming record and coding skills in at least two of the above languages. Good knowledge of statistical and machine learning methods is also essential. Other essential characteristics include: ability to plan and organize work independently, commitment to user-friendly coding, excellent communication and interpersonal skills.
This research position will be based in the Department of Economics, within the Faculty of Social Sciences and is tenable from 1 July 2023, or as soon as possible thereafter. Depending on a candidate's circumstances, a part-time status may also be negotiable.
Applications will be considered from candidates who are working towards or nearing completion of a PhD in Economics. The title of Research Fellow will be applied upon completion of PhD. Prior to the PhD qualification being awarded the title of Senior Research Assistant will be given.
Informal enquiries may be addressed to Professor Jean-Yves Pitarakis (email: email@example.com)
We are committed to equality, diversity and inclusion and welcome applicants who supports our mission of inclusivity.
Apply by midnight on the closing date. For assistance contact Recruitment on +44(0)2380 592750 or firstname.lastname@example.org quoting the job number.
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