Research Assistant or Research Fellow in Bioinformatics

Cranfield University
Cranfield
11 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Scientist

Graduate Clinical Data Analyst

Research Assistant/Associate in Exoplanetary Remote Sensing and Data Science (up to 2 posts) (F[...]

Air Quality & Data Science Professor — Research & Teaching

Research Assistant in Medical Data Science

Materials AI Research Assistant — Datasets, NLP & APIs

Role Description

We are seeking a passionate and skilled researcher to join our groundbreaking research on climate-informed food safety and pathogen impact modeling at Cranfield University.

About the Role

You will join the Bioinformatics genomic informatics team as part of the Horizon-Europe’s . The project aims to enable for the first time a holistic, systemic approach to food safety risk assessment across the supply chain in view of climate change models with the use of digital technologies, including AI.

This role involves leading innovative research to develop climate-informed impact models for enteric pathogens in fresh produce and mycotoxin contamination in short-grain cereals under varying climate scenarios. You will conduct climate-controlled experiments to study mycotoxin production, generate transcriptomic profiles using RNA-Seq, and identify key mycotoxin-producing gene clusters. Leveraging integrated transcriptomic and climate data, you will develop and optimize predictive models for forecasting mycotoxin levels, ensuring precision beyond traditional approaches. The role also involves collaborating with international partners, contributing to teaching activities, and disseminating research findings through high-impact publications and conferences.

About You

You will have a PhD in Bioinformatics, Systems Biology, Microbiology, Molecular Biology, or a related field (or be close to completion). For Research Assistant, you will have an MSc in Bioinformatics or related fields with demonstratable experience in genomic and transcriptomic analysis. You should demonstrate expertise in designing and conducting growth chamber experiments, as well as bioinformatics skills for RNA-Seq transcriptomic analysis, including assembly, differential expression, and functional annotation. Experience with molecular biology techniques and a strong understanding of Fusarium species and mycotoxin contamination mechanisms are ideal. Proficiency in using high-throughput sequencing technologies, computational tools, and scripting languages (e.g., Python, R) is required. Familiarity with predictive modeling techniques and integrating climate data with biological data will be advantageous.

About Us

As a specialist postgraduate university, Cranfield’s world-class expertise, large-scale facilities and unrivalled industry partnerships are creating leaders in technology and management globally. Learn more about Cranfield and our unique impact .

The Bioinformatics Group at Cranfieldis a computer-based group with research focusing on the development and application of computational methods and AI in order to unravel the complexity of biological systems. We run and administer our in-house high-performance-computing facility for NGS data analysis, including de-novo assembly, global transcriptomics, and genotyping. We also have a long track record in data science and machine learning.

Our Values and Commitments

Our shared, stated values help to define who we are and underpin everything we do: Ambition; Impact; Respect; and Community. Find out more .

We aim to create and maintain a culture in which everyone can work and study together and realise their full potential. We are a Disability Confident Employer and proud members of the Stonewall Diversity Champions Programme. We are committed to actively exploring flexible working options for each role and have been ranked in the Top 30 family friendly employers in the UK by the charity . Find out more about our key commitments to Equality, Diversity and Inclusion and Flexible Working .

Working Arrangements

Collaborating and connecting are integral to so much of what we do. Our Working Arrangements Framework provides many staff with the opportunity to flexibly combine on-site and remote working, where job roles allow, balancing the needs of our community of staff, students, clients and partners.

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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.