Job offer in england PhD Studentship – Strategic Development of the Innovative In-line Plankton Image Analysis (PIA) System to Fit Policy and Ecosystem Modelling Data Needs (CASE studentship with Cefas) (PITOIS_UCEFAS18EE) at University of East Anglia

Start Date: October 2018

No. of positions available: 1

Hours: Full time or part time

Supervisor: Dr Sophie Pitois

Project description: Scientific Background

Zooplankton are critical in the good functioning of marine food webs and sensitive to environmental changes, but knowledge of their biomass, size composition and production rates remains fragmented. Essentially this marine ecosystem compartment remains poorly assessed because of the high cost of traditional monitoring approaches of net deployment, preservation and microscopy.  In the context of limited resources, cost-efficient methods to increase the spatio-temporal sampling scale and integrate plankton monitoring into multipurpose surveys are urgently needed.


The Plankton Image Analyser (PIA) is a new high-speed, colour line scan-based, automated imaging instrument under development in the Culverhouse group, Plymouth University. The results of recent sea trials on the RV Cefas Endeavour demonstrate the PIA’s great potential as part of the integrated monitoring program currently being developed at Cefas with the aim of informing future fisheries and environmental policy.


Working at the Science/Policy interface, the PhD student will advance the development of the PIA to answer the fisheries and environmental policy needs. Specifically, the student will:

  1. Collect plankton data with PIA during surveys on-board RV Cefas Endeavour.
  2. Actively and strategically develop PIA to fit policy and ecosystem modelling data needs.
  3. Use data from PIA and other plankton monitoring programs (e.g. CPR) to build a plankton observatory that by integrates long-term and large-scale data and small-scale high resolution data.
  4. Use Cefas survey data and statistical modelling techniques to link zooplankton data with data for lower (primary producers) and upper trophic levels.


Based at Cefas, the student will receive training on the PIA instrument, seagoing, plankton sampling, taxonomy, statistical and ecosystem modelling. The supervisory team are experts in zooplankton ecology, biological oceanography and computer vision & robotics, and there will be opportunities for interacting with policy makers. He/she will develop a range of transferable skills, critical thinking, and the ability to analyse complex information.

This project has been shortlisted for funding by the EnvEast NERC Doctoral Training Partnership, comprising the Universities of East Anglia, Essex and Kent, with over twenty other research partners. Undertaking a PhD with the EnvEast DTP will involve attendance at mandatory training events throughout the course of the PhD.

Shortlisted applicants will be interviewed on 12/13 February 2018.

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Person specification: This PhD would suit students with a degree in Marine, Environmental, Ecosystem Sciences or numerate discipline and with keen interests in the marine environment and instrumentation. Self-motivated, enthusiastic candidates with experience of computer-based analysis, programming and interest in policy-relevant research are ideal.

EnvEast welcomes applicants from quantitative disciplines who may have limited background in environmental sciences. Excellent candidates will be considered for an award of an additional 3-month stipend to take appropriate advanced-level courses in the subject area.

Minimum entry requirement: 2:1 or equivalent.

Funding notes: Successful candidates who meet RCUK’s eligibility criteria will be awarded a NERC studentship – in 2017/18, the stipend is £14,553. In most cases, UK and EU nationals who have been resident in the UK for 3 years are eligible for a stipend. For non-UK EU-resident applicants NERC funding can be used to cover fees, RTSG and training costs, but not any part of the stipend. Individual institutes may, however, elect to provide a stipend from their own resources.


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