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Administrative Work

Employer
UNIVERSITY OF SOUTHAMPTON
Location
Southampton, United Kingdom
Salary
Please consult your hiring manager for pay rate
Closing date
20 Mar 2023

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Public Engagement

Location:  Highfield Campus
Salary:   Please consult your hiring manager for pay rate
Closing Date:  Monday 20 March 2023
Reference:  U2195623TW

Start Date:  As soon as possible following successful interview.

End Date: 10- 12 weeks after start date.

Location: Highfield Campus

Hours: 40 hours over a 12 week period. 

Job Purpose: 

Develop a predictive model for the next UK general election, with a focus on how it will play out in individual constituencies, especially in Hampshire. This entails a) a model to simulate party vote shares based on current polling and b) a model to translate votes to seats on the new constituency boundaries, using local election data. Draw up a short report on the findings for Public Policy Southampton.

Key Accountabilities/Responsibilities: 

  • Create and apply a model for constituency-level predictions.
  • Create and apply a model for the national popular vote.
  • Identify, review and combine input datasets.
  • Develop a report about the model’s predictions for the Hampshire area.
  • Any other duties as allocated by the line manager following consultation with the post holder.

Essential Skills: 

  • Attained a Masters or equivalent in the social sciences.
  • Experience with original data-driven research.
  • Good competency with STATA statistical software. 
  • Ability to locate, merge and append datasets.
  • Experience presenting data in an accessible form.
  • Able to effectively organise allocated work activities.
  • Able to work well with minimum supervision.
  • Able to independently solve a range of problems.
  • Able to work to a set deadline.
  • Able to seek and clarify detail.

Desirable Skills: 

  • Attained or studying for a PhD or equivalent in the social sciences.
  • Competence in regression, predict and loop functions in STATA. 
  • Familiarity with applied Bayesian methods.
  • Familiarity with simulation methods.
  • Familiarity with Geographic Information Systems (GIS) such as ArcMap.

 Please note that unfortunately we can not accept Certificate of Sponsorship (COS) for Casual Work at the University of Southampton. 

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