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Posted 19 days ago

RESEARCH FELLOW IN ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING FOR SCIENTIFIC DISCOVERY

@ The University of Manchester

Ontario

Full-time
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Overview

The University of Manchester is hiring a full-time research fellow to develop and apply machine learning and AI to protein engineering and enzyme design within the Chica Research Group. The work involves analysing biological and chemical datasets, building predictive models and computational tools, and collaborating across disciplines. The posting lists a generous pension, 29 days annual leave plus bank holidays, and ride-to-work and EV car schemes.

Responsibilities:

  • Develop and apply machine-learning approaches to protein engineering
  • Analyse and model large biological and chemical datasets
  • Design, train and evaluate predictive models
  • Build computational tools and workflows
  • Provide AI and machine-learning guidance across the group

Requirements summary:

  • Expertise in AI, machine learning or a quantitative discipline
  • Experience with data-driven modelling and software development
  • Interest in interdisciplinary collaboration
  • Chemistry or biology experience is an advantage
Source and dates

Source type not verified · apify-linkedin

Employer posting date
2026-10-26
First seen by our source
2026-11-14
Source record updated
2026-11-14

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Job details

SeniorityMid level
DepartmentResearch & science
Hours per week40 (estimated)
Work settingOffice, Laboratory
PositionMostly sitting
Physical demandsphysical low · computer high
LanguagesEnglish
EducationDoctorate (preferred)
Fields of studyArtificial intelligence, Machine learning, Computer science, Applied mathematics, Statistics
Perks mentionedRetirement plan

Summary and details written by AI from the posting; the employer’s posting is the authority.

The University of Manchester

FieldValue
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Job description
The Chica Research Group, based within the Manchester Institute of Biotechnology and the Department of Chemistry at the University of Manchester, develops computational and experimental approaches for protein engineering and enzyme design.

We are seeking an outstanding researcher with expertise in artificial intelligence, machine learning, computer science, applied mathematics, statistics, or a related quantitative discipline to join our highly interdisciplinary research environment.

The successful candidate will work closely with computational and experimental researchers to develop and apply modern data-driven approaches to challenges in biomolecular design and engineering. Prior experience in chemistry, biology, or protein science is advantageous but not required.

This position offers an exciting opportunity to contribute to the development of next-generation computational approaches for scientific discovery while helping to expand AI and machine-learning capabilities within the research group.

Overall Purpose of the Job

The postholder will develop and apply machine-learning and artificial-intelligence approaches to challenges in protein engineering and enzyme design.

Working closely with researchers across the group, the successful candidate will analyse complex biological, chemical, and experimental datasets; develop predictive models and computational tools; and identify opportunities where machine learning and artificial intelligence can accelerate scientific discovery.

The role offers substantial scope for methodological innovation and provides an opportunity to contribute to the future development of AI-enabled research within the group.

You will be responsible for:

  • Developing and applying machine-learning approaches to challenges in protein engineering and enzyme design.
  • Analysing, integrating, and modelling large biological, chemical, and experimental datasets.
  • Designing, implementing, training, and evaluating predictive machine-learning models.
  • Developing computational tools, workflows, software, and methodologies that support data-driven scientific discovery and expand the group's computational capabilities.
  • Providing specialist expertise, guidance, training, and support in machine learning, data science, and artificial intelligence across the research group.
  • Collaborating with researchers from diverse disciplinary backgrounds to identify and address scientific challenges using AI and machine-learning approaches.
  • Working closely with postdoctoral researchers, postgraduate students, and other team members on computational and experimental projects.
  • Contributing to collaborative research projects, publications, conference presentations, and funding applications.
  • Maintaining high standards of software development, documentation, and reproducible research.
  • Contributing to the strategic development of the group's computational and AI research activities.
  • Keeping abreast of developments in artificial intelligence, machine learning, data science, and scientific computing.

We are particularly interested in applicants who:

  • Enjoy working in highly collaborative and interdisciplinary research environments.
  • Are motivated to develop innovative computational approaches to scientific challenges.
  • Are enthusiastic about learning new technologies and methods and applying them to frontier research problems.

Our benefits include:

  • Generous employer contribution pension
  • 29 days annual leave plus bank holidays, along with Christmas closure
  • Ride to work and EV car scheme available

For more information, please see University of Manchester Benefits. You can also find information on our Flexible and Hybrid working here.

We are an open place of enquiry and challenge. We embrace and celebrate difference, diversity and debate, and we pride ourselves on being a place of education, learning and community where we are able, within the law, to question and test received wisdom, express new ideas and explore controversial or unpopular topics and opinions. Find out more from our Freedom of Speech Policy.

Enquiries About The Role, Shortlisting And Interviews

Name: Roberto Chica

Email Address: [email protected]

General enquiries and administrative support

[email protected]

Technical and job portal support

https://knowledge.jobtrain.co.uk/jobseeker [knowledge.jobtrain.co.uk]

Applications close at midnight on the closing date.

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