We are made up of a dynamic and vibrant community focused on solving challenging long-term marine science problems, underpinning international and UK public policy, business and societal outcomes.
The ocean has the potential to provide the solutions to so many of the social, economic and environmental challenges we face worldwide. To truly harness the value of the ocean, we put ocean research, science and discovery at the heart of our culture.
Join us in shaping the future of oceanographic research and contribute your unique perspective to our organization.
About the role
We are seeking to recruit a Research Scientist in Marine Ecology and Machine Learning.
Marine microbial ecosystems are tremendously diverse, with substantial implications for how they modulate and are affected by global biogeochemical cycles and climate change. Although novel datasets are expanding our understanding of microbial ecosystems and how they affect carbon uptake and storage, we still struggle to model them adequately. Machine Learning/Artificial Intelligence presents an exciting opportunity to use the ever-increasing datasets to explore the interactions between ecosystems and biological carbon cycles.
You will investigate observations and model output using ML/AI to explore topics such as how tipping points are triggered in marine ecosystems, and how plankton diversity influences the biological carbon pump. You will have the opportunity to explore both fundamental and practical aspects of this work, and to pursue your own related research questions. Through this work you will have the opportunity to substantively improve our ability to understand and predict the interactions between ocean biogeochemistry and marine ecosystems.
You will be part of the Biological Carbon Cycles group. We are a diverse, dynamic, and highly collaborative group of scientists investigating a broad range of topics, including the biological pump, autonomous vehicles, computer vision, and combining observations with models. You will also have the opportunity to collaborate with NOC’s Ocean Informatics group, and so have the chance to interact with the full range of ML/AI research at NOC. NOC itself is a fantastic place to work as a research scientist, with a unique combination of benefits. Outside of NOC, you will be working within large, world-class collaborative consortia, through which you will be able to expand your professional network and have access to expert support in ML/AI, observational datasets and numerical modeling.
The successful candidate will be expected to conduct research and write papers. At your discretion, you will also have the opportunity to be involved in a wide range of other career development activities, such as presenting at conferences, writing proposals, and supervising students.
About you
We are looking for candidates who:
- Hold a Ph.D. or equivalent in oceanography or a related quantitative field (e.g. physics, computer science, statistics, environmental science…).
- Have demonstrable experience with machine learning methods. Classical ensemble and margin classifiers to modern neural networks and transformers are all relevant.
- Have an understanding of ocean biogeochemistry or marine ecology research.
- Have a publication record commensurate with their experience.
- Enjoy collaborating with colleagues, but also working independently.
Why NOC?
We offer a generous set of benefits, including:
- 30 days contractual annual leave, plus 3.5 extra closure days and bank holidays
- A 10% employer contribution pension scheme
- Access to our Employee Assistance Programme, offering free and anonymous support on mental, physical, emotional, health and financial issues
- Access to a flexible benefits portal offering online discounts, cashback and eGift cards
- A Cycle2Work scheme allowing employees to acquire bikes and accessories
- A great working environment with a number of social events, including summer and Christmas celebrations
- We are proud to be a Living Wage Employer
Location
This position will be based in Southampton. The centre is well connected by public transport and has ample cycle parking in addition to free onsite car-parking with over 40 EV charging points.
We have a hybrid working approach where for most positions staff can work from home up to 2 days per week. If you are interested in this position, but require a more flexible working arrangement, please contact the recruitment team using the contact details below.
We can support visa applications where required. We may be able to offer financial support for applicants who will need to relocate for this position.
Date advert posted: 8 August 2025.
Closing date: 5 September 2025.
