Back to search results

Research Associate in Biostatistics

University of York - Department of Biology

Location: York
Salary: £32,817 to £40,322 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 14th April 2021
Closes: 26th May 2021
Job Ref: 9296


Applications are invited for a Postdoctoral Research Associate to work on a BBSRC-funded study focussed on uncovering the genetic basis by which plants respond to changes in day length to produce synchronised flowering.  It is led by Dr. Daphne Ezer, Lecturer in Computational Biology (Department of Biology, University of York), Dr. Marina Knight (Department of Mathematics, University of York) and Prof Seth Davis (Department of Biology, University of York).


You will develop and apply new statistical methods to identify genetic loci that are associated with the ability of a plant to quickly detect changes in day length.  Ideally, you should have some familiarity with time series (or, even better, functional) data, Fourier analysis, and/or biostatistical methods (such as those used in quantitative trait loci mapping). 

You will work in close collaboration with other group members on the project, and the position will include training in modern plant sciences and molecular-imaging techniques.

The long-term aim of the project is to develop more efficient breeding strategies to produce crop lines that have synchronised development, by screening plant seedlings for varieties that respond quickly to changes in day length (and therefore respond in a more uniform way to the change in seasons).  It is important for plants to develop in a synchronised manner to reduce food waste, since farmers harvest whole fields at a time and throw away produce that does not meet food standards.

Skills, Experience & Qualification needed


  • First or second degree in Maths, Statistics, Computer science, Physics or Biology
  • PhD in a mathematical or scientific area involving data analysis or equivalent experience
  • Knowledge in [at least one of the following (i) functional data analysis or Fourier analysis (ii) time series analysis (iii) quantitative genetics, such as Quantitative Trait Locus (QTL) mapping].
  • Knowledge of a range of research techniques and methodologies, including programming (R, Matlab or Python) and ability to develop new statistical methods or tools
  • Highly developed communication skills to engage effectively with an interdisciplinary team, both orally and in writing.
  • Ability to write up research work for publication in high profile journals
  • Competency to make presentations at conferences or exhibit work in other appropriate events
  • Competency to conduct individual and collaborative research projects


  • Has research expertise or interest in plant biology or genetics.
  • Ability to identify sources of funding and contribute to the process of securing funds, with collaborators if required

Interview date: Wednesday 23 June 2021

For informal enquiries: please contact Dr. Daphne Ezer at and/or Dr. Marina Knight at

The University is committed to promoting a diverse and inclusive community  – a place where we can all be ourselves and succeed on merit. We offer a range of family friendly, inclusive employment policies, flexible working arrangements, staff engagement forums, campus facilities and services to support staff from different backgrounds.

 A place where we can ALL be ourselves #EqualityatYork

We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:

Subject Area(s):


Job tools
More jobs from University of York

Show all jobs for this employer …

More jobs like this
Join in and follow us

Browser Upgrade Recommended has been optimised for the latest browsers.

For the best user experience, we recommend viewing on one of the following:

Google Chrome Firefox Microsoft Edge