Research Fellow in Probabilistic Tsunami Risk Analysis and Impact Forecasting (PCTWIN)

UCL Eastman Dental Institute
London
1 year ago
Applications closed

Related Jobs

View all jobs

Postdoctoral Fellow- Computational Biology and Machine Learning

Postdoctoral Fellow- Computational Biology and Machine Learning

Machine Learning Engineer Apprentice

MSc Data Science and Artificial Intelligence

Remote Online Data Analyst Bengali Speakers in UK

Remote Online Data Analyst Bengali Speakers in UK

About the role

PCTWIN (People-Centred Tsunami Early Warning for the Indian Coastlines)
The “People-Centred Tsunami early Warning for the Indian coastlines (PCTWIN)” is a 4-year (£ grant funded by NERC UKRI and the Indian Ministry of Earth Sciences (MoES), started on 15/02/. It is led by University College London (UCL)’s Department of Risk and Disaster Reduction (RDR), and Indian National Centre for Ocean Information Services (INCOIS), Hyderabad. This collaborative project involves the core team, UCL, INCOIS, University of Edinburgh, Institute of Seismological Research (ISR) India, and Norwegian Geotechnical Institute (NGI). Furthermore, the project involves as international partners, the Helmholtz-Centre Potsdam - GFZ German Research Centre for Geosciences, Universidad de Málaga (UMA), Earth Observatory of Singapore, Intergovernmental Oceanographic Commission of UNESCO, Odisha State Disaster Management Authority (OSDMA), and Kerala State Disaster Management Authority (KSDMA). As advisory board, the project has representatives from the UCL Warning Research Centre (WRC), Intergovernmental Coordination Group for the Indian Ocean Tsunami Warning and Mitigation System (ICG/IOTWMS), Istituto Nazionale di Geofisica e Vulcanologia (INGV), Geoscience Australia (GA), and International Research Institute of Disaster Science (IRIDeS) at Tohoku University.
PCTWIN conducts research informed by understanding of disasters and by local knowledge. It aims to:
1. Improve the understanding of and address knowledge gaps in the fundamental properties and physics of tsunamigenic earthquake and landslide processes.
2. To improve detection and forecasting of tsunamis and to provide more effective and more inclusive tsunami warnings.
3. Use participatory methods to make the tsunami warning chain more inclusive and To increase preparedness to respond to tsunamis.

About you

We are seeking a candidate with a PhD (or be close to completion) in Civil Engineering, Geo-informatics, Geography, Earth Sciences, or a relevant field. They should be familiar with probabilistic tsunami hazard and risk analysis, and the tsunami early warning systems (TEWS). Experience of working with spatial data, Geographical Information System (GIS), probabilistic and machine learning skills, and coding experience with Python are highly desirable. The successful applicant will also have excellent written and verbal communication skills in English to a wide variety of audiences; computer and software skills; organisational and independent working skills. They should be able to work collaboratively with a diversity of colleagues and students; have a commitment to high quality research; contribute to scientific and popular science dissemination; and contribute to the RDR multidisciplinary and multi-cultural intellectual environment.

What we offer

As well as the exciting opportunities this role presents, we also offer some great benefits some of which are:
• 41 Days holiday (27 days annual leave 8 bank holiday and 6 closure days per annum) per annum
• Additional 5 days' annual leave purchase scheme
• Defined benefit career average revalued earnings pension scheme (CARE)
• Cycle to work scheme and season ticket loan
• Immigration loan
• Relocation scheme for certain posts
• On-site gym
• Enhanced maternity, paternity and adoption pay
• Employee assistance programme: Staff Support Service
• Discounted medical insurance.
To find out more, visit

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

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Jobs

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.

🍪 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.