Accelerating Enzyme Evolution for Chemical Development: Intelligent Navigation of the Sequence Space - 3 year fixed term contract
| ABG-139561 | Thesis topic | |
| 2026-06-15 | EU funding |
- Biochemistry
- Biotechnology
Topic description
A doctoral position is available for 3 years to work with AstraZeneca (Pharmaceutical Sciences, Early Chemical Development, Biocatalysis Team) and Professor Florian Hollfelder at the Biochemistry Department of Cambridge University (https://hollfelder.bioc.cam.ac.uk/).
We are currently seeking to recruit a doctoral candidate to help accelerate enzyme discovery for biocatalytic applications. Even with advanced tools, directed evolution timelines often remain slower than increasingly rapid compound manufacturing campaigns and faster workflows are needed to find efficient enzymes for sustainable chemical processes and ultimately support the rapid delivery of medicines to patients. This project will speed up the discovery process by functional metagenomics and directed evolution in approaches that combine wet lab and in silico approaches using droplet microfluidics (Chem Rev. 2023; 123(9):5571-5611. doi: 10.1021/acs.chemrev.2c00910), next-generation sequencing, and machine learning.
The project is part of the Horizon Europe EU Marie Curie Network MetaExplore (www.metaexplore.eu/) and involves collaborations with various EU and UK groups on harnessing environmental sources for novel biocatalysts that may play a role in future sustainable processes with higher resource and energy efficiency. The MetaExplore training programme will equip young researchers with computational and experimental skills to integrate both productively.
For more information about MetaExplore, please visit: https://metaexplore.eu/
Starting date
Funding category
Funding further details
Presentation of host institution and host laboratory
The PhD will be a collaboration between Astrazeneca (Cambridge) and the Hollfelder group, Department of Biochemistry, University of Cambridge (https://hollfelder.bioc.cam.ac.uk)
Website :
PhD title
Country where you obtained your PhD
Institution awarding doctoral degree
Graduate school
Double degree
YesCountry where the PhD was obtained in cotutelle
Establishment awarding the doctorate in cotutelle
Candidate's profile
Enzymology, Molecular Biology, Chemical Biology, Bioinformatics interest.
Key responsibilities:
(i) On the experimental side: using a range of tools from chemical, molecular and synthetic biology to generate and screening large and diverse DNA libraries using ultrahigh-throughput technologies for the discovery novel enzymes for sustainable biocatalytic processes.
(ii) On the computational side: unprecedented availability of sequence data (e.g. >6.5 billion ORFs in the database MGnify) and machine learning will provide systematic insights via in silico sequence interpretation using custom-made algorithms. The MetaExplore network will harness the diversity of nature and the power of machine learning and AI.
The candidate must not have resided in the UK for more than 12 months in the past 3 years
Essential skills:
* Educated to a first (or upper second) class degree in Chemistry, Biochemistry or a related relevant subject.
* Familiarity with experimental molecular and chemical biology techniques such as recombinant protein expression and related molecular biology and protein engineering methods.
* A passion for biocatalysis and for applying new technologies.
* An interdisciplinary and collaborative research approach.
* Developing bibliography of research publications.
* Experience of leading your own work & research.
Desirable:
* Awareness of wider application of biocatalysis in pharma.
* Experience in DNA library preparation.
* Experience in assay development.
* Experience in high-throughput screening and analysis of large datasets.
* Experience in bioinformatics and especially AI/ML.
* Experience in next-generation sequencing.
* Experience in UPLC and SFC.
* Experience in microfluidics.
* Excellent communication skills across interfaces of subject area and expertise, both internally and externally.
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