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Bioinformatics (synthetic biology) PhD Projects, Programs & Scholarships

We have 59 Bioinformatics (synthetic biology) PhD Projects, Programs & Scholarships

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  Combining Synthetic Biology and Modelling to Understand and Predict Evolution
  Dr M Lagator, Dr J-M Schwartz
Applications accepted all year round

Funding Type

PhD Type

Mutations, and their effects on organismal fitness, lie at the heart of understanding and predicting evolution. Because of its central role in determining evolutionary outcomes, much experimental and theoretical effort has been put into describing the fitness effects of mutations.
  Using synthetic biology to understand the evolution of antibiotic resistance
  Dr M Lagator, Dr C Knight
Applications accepted all year round

Funding Type

PhD Type

Imagine an architect, tasked with converting an old stadium into a building with a different function, without demolishing it.
  EASTBIO Advanced model-based optimization of biomolecular systems.
  Research Group: Institute of Quantitative Biology, Biochemistry and Biotechnology
  Dr D Oyarzun
Application Deadline: 5 January 2020

Funding Type

PhD Type

We are looking for an excellent doctoral student to join us on a project at the interface of computational optimization and synthetic biology.
  4-year PhD Studentship in Synthetic Biology for the Rational Reprogramming of Living Cells
  Dr T Gorochowski, Dr L Marucci
Application Deadline: 30 November 2019

Funding Type

PhD Type

The ability to reprogram living cells would open up opportunities to repurpose biology and tackle major challenges covering the sustainable production of material to the development of living therapeutics [1].
  Engineering tRNA neochromosomes in yeast
  Prof P Cai, Prof D Delneri
Applications accepted all year round

Funding Type

PhD Type

Advances in DNA synthesis technology have led to rapid growth in the field of synthetic biology, heralding a nascent era of synthetic genomics.
  (BBSRC DTP) Predictive Genotype-Phenotype-Fitness Mapping in E.coli
  Dr M Lagator, Dr J-M Schwartz, Dr P Day
Application Deadline: 31 January 2020

Funding Type

PhD Type

Genotype-phenotype-fitness mapping, or the connection between genetic mutations and their effects on organismal fitness, lies at the heart of understanding and predicting evolution.
  Automating large-scale gene circuit design towards programmable cellular computers
  Research Group: Institute of Quantitative Biology, Biochemistry and Biotechnology
  Dr Baojun Wang
Application Deadline: 5 January 2020

Funding Type

PhD Type

Bacterial cells live in an ever changing environment and therefore are equipped with specific genetically-encoded sensors and signalling networks to continuously perceive and process the various environmental signals.
  EASTBIO Automating large-scale gene circuit design towards programmable cellular computers
  Research Group: Institute of Quantitative Biology, Biochemistry and Biotechnology
  Dr Baojun Wang, Dr D Oyarzun
Application Deadline: 5 January 2020

Funding Type

PhD Type

Bacterial cells live in an ever changing environment and therefore are equipped with specific genetically-encoded sensors and signalling networks to continuously perceive and process the various environmental signals.
  Discovery and characterisation of new antibiotics from uncultivated microbes.
  Dr J Owen
Applications accepted all year round

Funding Type

PhD Type

Recent developments in DNA sequencing technology have greatly enriched our understanding of the microbial world. By directly sequencing DNA extracted from communities of environmental microbes, we have been able to observe a hidden majority of microbial species that cannot be readily grown in the laboratory.
  EASTBIO Unravelling mechanisms controlling gene expression noise in S. cerevisiae during rapid adaptive responses and its application to biotechnology.
  Research Group: Institute of Quantitative Biology, Biochemistry and Biotechnology
  Dr S Granneman
Application Deadline: 5 January 2020

Funding Type

PhD Type

Microbes are constantly subjected to changes in their environment and have to rapidly alter their transcriptome to adapt efficiently.
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