Senior Scientist - Radar Altimetry or SAR specialist

NPL
Teddington
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Higher/Senior Scientist in Quantum Computing and Machine Learning

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

NPL is the UK’s National Metrology Institute. Our role is to research, create and deliver the measurement infrastructure which underpins the UK’s prosperity and quality of life across many fields of industry.  The National Physical Laboratory (NPL) is seeking an experienced Senior Research Scientist to join our team in Teddington.

The Climateand EarthObservation(CEO)groupat NPL is a world leader in the theory,methods,and practice of metrological(measurement science)traceability ofEarthObservation(EO)instrumentation and their data products.CEO projectscover the metrology and quality assurance of satellitedata products – from the pre-flight calibration and onboard processingto the higher-level data products providing essential climate variables and other societal datasets. We also develop in-situ fiducial reference measurement (FRM) techniques for calibration and validation of satellite data products.We collaborate strongly with other teams within NPL, especially the Data Science team, and externally with a wide range of collaborators. 

 

Ourresearch programme in active satellitesensors(radar altimeters and related technologies)is growing rapidly, with recently wonprojects looking at the uncertainty assessmentandcharacterisation metrics for radar altimetry(including both the altimeter and the microwave radiometer)onCopernicus Sentinel 6, Sentinel3,and CRISTAL missions, along with the development ofsuitableFRMs, for oceans,inland water, sea ice and land icesurfaces. We have alsorecently started projects that consider how observational uncertainties can be used in Earth systems modelling. Weare looking to expand our efforts with suchactivesensors, and to develop new capability relating to SAR-mode processing(fully focused and interferometric)of radar altimeters. Additionally, weare keen to explore the metrological aspects of SAR itself, especially where SAR observations are complementary to our active research projects on vegetation and Nature Based Solutions. 

  

Some of the day to day duties and responsibilities of the Senior Scientist will involve:

Leading cutting-edge research, recognising aspects that could be commercially viable
Representing NPL to promote our work and raise our profile
Crafting winning bids, in line with NPL’s growth strategy
Working inclusively and collaboratively to develop partnership opportunities

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.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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.