03/07/2018
The Human Resources Strategy for Researchers

Using machine learning to optimise biofuel and industrial compound production in cyanobacteria (LEASMITH_U18ICASENF)

This job offer has closed


  • ORGANISATION/COMPANY
    University of East Anglia
  • RESEARCH FIELD
    Biological sciences
  • RESEARCHER PROFILE
    First Stage Researcher (R1)
  • APPLICATION DEADLINE
    23/08/2018 23:00 - Europe/London
  • LOCATION
    United Kingdom › Norwich
  • TYPE OF CONTRACT
    Other
  • JOB STATUS
    Other

Cyanobacteria (oxygenic photosynthetic bacteria) are potential biotechnology platforms, since they can convert carbon dioxide into biofuels and industrial/pharmaceutical chemicals using energy derived from sunlight. This technology offers the opportunity to limit carbon emissions from industry while replacing petroleum derived compounds with renewable alternatives. However, commercialisation is dependent on improved understanding of cyanobacterial metabolism. In collaboration with Dr Dongda Zhang (University of Manchester) and Simon Moxon (UEA) the student will apply machine learning approaches to investigate cyanobacterial metabolism and identify optimal pathways and metabolic fluxes for compound production. The student will test these outcomes by generating appropriate mutants and measuring growth and compound production of these strains in small reactors. Commercially relevant mutants will then be tested in larger industrial reactors in collaboration with our industrial partner, Cyanetics Ltd, using carbon dioxide emissions from industrial plants. The ideal candidate for this project will have a background in chemical engineering, bioengineering, computer science, or molecular biology/microbiology with programming skills. The student will join a cyanobacterial biology laboratory with strong national and international links. Examples of recent publications from the investigator include: Saar et al (2018) Nature Energy 3 (1) 75; Lea-Smith et al (2016) Plant Phys. 172(3):1928-1940; Lea-Smith et al (2015) PNAS 112(44):13591-6; Lea-Smith et al (2014) Plant Phys. 165(2):705-714. This project offers the opportunity to develop skills in machine learning, molecular biology, microbiology and chemical engineering which will aid a future career in academia or industry.
This National Productivity Investment Fund (NPIF) Industrial CASE project, aligned to the Industrial Grand Challenge theme of Artificial Intelligence and the Data-Driven Economy, has been selected for funding by the BBSRC Norwich Research Park Biosciences Doctoral Training Partnership (NRPDTP). Shortlisted applicants will be interviewed on the 2nd August 2018.
Through collaboration with a non-academic partner, iCASE students will spend 3-18 months on a placement with the partner company. Through this placement, students gain access to training, facilities and expertise not available in an academic setting alone, significantly enhancing future employability.
The NRPDTP offers postgraduates the opportunity to undertake a 4-year research project whilst enhancing professional development and research skills through a comprehensive training programme. You will join a vibrant community of world-leading researchers. Students with, or expecting to attain, at least an upper second-class honours degree, or equivalent, are invited to apply.
For further information and to apply, please visit our website: http://biodtp.norwichresearchpark.ac.uk/the-programme/industrial-case

 

Funding Notes

Studentship covers a stipend (£14,777: UKRI 18/19 rate), research costs and tuition fees at UK & EU rate, and are available to UK/EU students who meet the UK residency requirements.

Students from EU countries who do not meet the UK residency requirements may be eligible for fees-only awards. Students in receipt of fees-only awards will be eligible for a maintenance stipend awarded by the NRPDTP Doctoral Scholarships Scheme, which when combined will equal a full studentship. To be eligible students must meet the EU residency requirements.
For funding eligibility guidance, please visit our website: http://biodtp.norwichresearchpark.ac.uk/how-to-apply/funding-and-eligibi...

Map Information

Job Work Location Personal Assistance locations
Work location(s)
1 position(s) available at
University of East Anglia
United Kingdom
Norwich

EURAXESS offer ID: 321211

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