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PhD studentship: Bioimage Analysis of Background Fluorescence in Cells

University of Bristol - Electrical & Electronic Engineering

Qualification Type: PhD
Location: Bristol
Funding for: UK Students, EU Students
Funding amount: £14,777
Hours: Full Time
Placed On: 2nd August 2018
Closes: 31st October 2018

The project: The Schools of Computer Science, Electrical and Electronic Engineering, and Engineering Maths (SCEEM) and Biochemistry at the University of Bristol, UK are looking for a PhD student interested in bioimage analysis of background fluorescence in cells.

All cells display some degree of autofluorescence. Although the molecular structures that display autofluorescence are characterised, a quantitative link between autofluorescence and cell state is not currently known [1]. By combining high-end microscopy techniques to detect the fluorescence pattern and intensity in cells with advanced image processing and machine learning tools [3,4,5], we aim to make precisely that correlation between the autofluorescence pattern and the physiological state of that cell.

This project will provide a novel image analysis tool for monitoring cell state. Whereas biosensors measure chemical biomarkers indicative, for example, of apoptosis (cell death), optical/imaging methods can better assess cell integrity and activity of individual cells (e.g., via morphology and autofluorescence) and detect “special” cells. In addition, by quickly measuring and analysing many cells, a statistically representative indication of the cell population in real time can be obtained.

We are looking for a person that thrives in an interdisciplinary environment. Either someone with a cell biological training but with a strong interest and expertise in image analysis or a person with a computational imaging / image processing background with exposure to life sciences research would fit the role profile. To highlight the interdisciplinary nature of the project the aims of the research project are as follows:

  • To detect the spectra, intensities, and localization of the autofluorescence in cells over time and during at different (induced) physiological states (e.g. oxygen stress, temperature).
  • To develop automated analysis tools for the detection changes in fluorescence pattern, signature, and/or intensities and classification into categories.
  • To register the autofluorescence categories with known cellular markers.
  • To correlate the classification groups identified in goal 2 with the physiological state as described above.
  • To design an imaging patch that could be used on cell culture bags

How to apply:  Please make an online application for this project at Please select <Electrical Engineering> on the Programme Choice page and enter details of the studentship when prompted in the Funding and Research Details sections of the form with the name of the supervisor Prof Alin Achim.

Candidate requirements:   A 1st or 2:1 honours degree equivalent at master level in electrical & electronic engineering, computer science, maths or biomedical subject.

Basic skills and knowledge required: Familiarity with scientific programming in Matlab/Python

Funding:  Scholarship covers full UK/EU (EU applicants who have been resident in the UK for 3 years prior to 1st September 2018) PhD tuition fees and a minimum tax-free stipend of £14,777 subject to confirmation.

Contacts:   Prof Alin Achim (

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