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PDRA in Machine Learning for High Impact Weather and Flood Prediction

University of Reading - Meteorology

Location: Reading
Salary: £30,395 to £39,609 per annum.
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 7th June 2019
Closes: 19th July 2019
Job Ref: SRF29169
 

The University of Reading invites applications for a postdoctoral research assistant to develop and evaluate machine learning techniques for processing observations of weather and flooding from datasets of opportunity, such as river cameras. The post is funded by the EPSRC project “Data Assimilation for the Resilient City” (DARE) – (https://research.reading.ac.uk/dare/). The goal of the project is to use Data Science tools and techniques to create a step-change in skill for numerical predictions of urban natural hazards. The research undertaken by the post holder will underpin quantitative use of urban observation data from diverse sources such as citizen science, crowdsourcing and internet of things. The successful candidate will be based at the University of Reading, Department of Meteorology but with close contact with colleagues in Computer Science.

You will have:

  • (or expect shortly to obtain) a PhD or equivalent experience, in computer science, a quantitative physical science, engineering or mathematics
  • knowledge of machine learning
  • the ability to write and adapt computer programs
  • experience giving oral presentations and writing scientific papers

Informal Contact Details
Contact role: DARE project PI
Contact name: Prof Sarah L Dance
Contact phone: +44(0)118 378 6452
Contact email: s.l.dance@reading.ac.uk

Alternative Informal Contact Details
Contact role: 
Co-supervisor
Contact name: Dr Varun Ojha
Contact phone: +44(0)118 378 8609
Contact email: v.k.ojha@reading.ac.uk

Interviews will be held on 14 August 2019.

The University is committed to having a diverse and inclusive workforce, is a Stonewall Diversity and Global Diversity Champion, and supports the principles of the Race Equality Charter and Athena SWAN. Applications for job-share, part-time and flexible working arrangements are welcomed and will be considered in line with business needs.

   
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