Mapping DNA damage and genome replication in malaria parasites with artificial intelligence and long-read sequencing

University of Cambridge
Cambridge
1 year ago
Applications closed

Related Jobs

View all jobs

Postdoctoral Research Assistant in Health Data Sciences

DataOps Engineer – Data Science Operations

Product Manager (Artificial Intelligence) - Ipswich, Norwich, Cambridge, Chelmsford

Research Fellow in Machine Learning for Hydroclimatology

Research Fellow in Machine Learning for Hydroclimatology

Data Science Apprentice (SPACE) - Pfizer

Applications are invited for a fully-funded 4-year PhD studentship based in the Department of Pathology at the University of Cambridge under the supervision of Dr Michael Boemo starting October 2025.

Malaria parasites replicate their genomes very differently to human cells, making genome replication an attractive therapeutic target for antimalarial drugs. The purpose of this research is to develop artificial intelligence software that leverages the power of long-read DNA sequencing to determine the genomic loci of DNA damage caused by these drugs and how this damage changes the movement of replication forks throughout the genome.

The student will have the opportunity to learn, or improve upon, the development of artificial intelligence for translational research in a supportive and collaborative environment.

More information about the Boemo Group is available at and .

Funding* will cover the student's stipend at the current Research Council rate and University Fees. The studentship will be funded for four years from October 2025. *The studentships are available to students who qualify for UK Home fees.

Applicants should hold (or expect to obtain) the equivalent of a UK 2.1 or higher in an undergraduate honours or Masters degree in a relevant subject. The studentship is open to those eligible for the Home rate of University fees.

Fixed-term: The funds for this post are available for 4 years in the first instance.

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

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

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.