Research Associate in Biostatistics

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Organisation
University of York
Locations

York, Heslington, United Kingdom

Application Deadline
Salary
£32,817-£40,322

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).

Role

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

Essential:

  • 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

Desirable:

  • 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 daphne.ezer@york.ac.uk and/or Dr. Marina Knight at marina.knight@york.ac.uk


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