Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Postdoctoral Data Scientist in Advanced Climate and Health Analytics

University of Oxford
Oxford
10 months ago
Applications closed

Related Jobs

View all jobs

Research Scientist (Quantum Chemistry and Machine Learning), London London

Research Scientist, Machine Learning (PhD)

Research Scientist, Machine Learning (PhD) London, UK • Software Engineering +1 more • Engineer[...]

Research Scientist (Quantum Chemistry and Machine Learning), London

Senior Genomic Data Scientist (we have office locations in Cambridge, Leeds & London)

Senior Genomic Data Scientist (we have office locations in Cambridge, Leeds & London)

Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, Windmill Road, Oxford, OX3 7LD The Oxford Planetary Health Informatics Lab is seeking a highly motivated Postdoctoral Data Scientist to support new Wellcome Trust funded projects on curation and modelling of harmonised climate and health datasets and co-creating publicly available decision-support dashboards and tools to enhance mapping, monitoring, and prediction of global health challenges including mitigating climate-exacerbated global health inequities. This position will be based at the Botnar Research Centre in Oxford. As a Postdoctoral Research Data Scientist, you will develop analysis plans, ethical protocols, standard operating procedures and undertake related literature reviews. You will analyse data following pre-specified analysis plans and approved protocols as well as curate and analyse real world climate/environment and health data assets. You will lead and support the drafting of scientific manuscripts, reports to funders and other materials for other audiences based on the results from research studies. You must hold a PhD/DPhil (or be near completion) in applied/medical statistics, bio/medical engineering, health data sciences, earth observation, environmental epidemiology, public health geography or another similar field. You must have demonstratable advanced skills in programming in R, Python, SQL, and/or similar languages alongside experience in version control e.g. Git; working knowledge of Docker, HuggingFace. Additionally, you will have demonstratable experience in data visualization and creating digital tools and dashboard using e.g. R Shiny, Power BI, Tableau or similar. You must have advanced taught or demonstrated skills in cleaning and analysing satellite-derived data analysis products and GIS data. Experience in the analysis of routinely collected (aka ‘real world’) health and climate data including and not limited to epidemiological, meteorological, environmental, earth observation data is desired. This is a full-time, fixed-term position for 2 years.

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.

Jobs

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.

Jobs

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.

Jobs

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.