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University of Cambridge

Research Assistant/Associate in Systems Microbiology

Cambridge
£33k – £46.1k/yr
Posted about 17 hours ago
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Research Assistant/Associate in Quantitative Bacteriophage Infection Models

We are seeking a creative and highly motivated Research Assistant/Associate to join Dr Somenath Bakshi's research group in the Department of Engineering. The project aims to develop quantitative, physiology-aware models of bacteriophage infection by combining high-throughput single-cell microscopy, microfluidics, image analysis, and mathematical modelling. The work will contribute to understanding how bacterial physiological state shapes phage infection dynamics and how this knowledge can be used to design more effective phage-based antimicrobial interventions. The successful applicant will work with a unique experimental platform developed in the Bakshi Lab (https://www.bakshilab.net/) that enables time-resolved measurements of individual bacterial cells throughout the phage infection process.

The post holder will be located in Central Cambridge, Cambridgeshire, UK.

The Role Involves

  • designing and carrying out quantitative single-cell infection experiments,
  • analysing large microscopy datasets
  • developing computational methods to extract infection dynamics from individual cells
  • integrating experimental observations with mathematical and statistical models of phage-host interactions.

The successful applicant will work closely with an interdisciplinary team spanning microbiology, engineering, and computation, and will contribute to developing predictive models that link bacterial physiology to infection outcome. They will also be expected to attend local seminars, journal clubs and group activities, present their work at conferences, and publish their research in leading scientific journals.

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Requirements

The successful applicant will have obtained, or be close to obtaining, a PhD in Microbiology, Systems Biology, Bioengineering, Biophysics, Biotechnology, Engineering, or a related discipline, together with experience in quantitative research within their field. Experience in one or more of the following areas would be advantageous: microbiology, bacteriophage biology, quantitative microscopy, image analysis, mathematical modelling, machine learning, or microfluidics. They will also have excellent communication, organisational and problem-solving skills, and a strong interest in interdisciplinary quantitative biology.

Appointment

Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded.

Salary Ranges

  • Research Assistant: £33,002 - £35,608
  • Research Associate: £37,694 - £46,049

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Fixed-term

The funds for this post are available for 3 years in the first instance.

How to Apply

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Please ensure that you upload your Curriculum Vitae (CV) and a covering letter [add up to 3 further documents needed e.g. research publication list] in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please submit your application by midnight on the closing date.

Contact

If you have any questions about this vacancy, please contact: Liz Elias, Group administrator email control-admin@eng.cam.ac.uk

For any technical questions about the vacancy, please contact Dr Somenath Bakshi at sb2330@cam.ac.uk.

Please quote reference NM50443 on your application and in any correspondence about this vacancy.

Equality, Diversity and Inclusion

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

Eligibility

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

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Skills

Microbiology
Bacteriophage Biology
Quantitative Microscopy
Image Analysis
Mathematical Modelling
Machine Learning
Microfluidics
Quantitative Research
Computational Methods
Statistical Models
Interdisciplinary Collaboration
Data Analysis
Experimental Design
Problem Solving
Communication Skills
Organizational Skills

Location

Cambridge, England, United Kingdom

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