Marie Sklodowska-Curie Actions Doctoral Network BlueOcean

University of Southampton; Southampton; On-site; GBP 44,000 - 47,000; Full time

Job summary

The University of Southampton invites applications for a First Stage Researcher position within the BlueOcean network. This PhD aims to develop robotic monitoring and data processing methods to document seafloor changes over large areas.

You will work with the Ocean Perception group on GNSS-denied environments, validate methods in simulation and with the Smarty200 AUV, and undertake secondments with partner institutions.

Qualifications

• Must not have a doctoral degree at the date of recruitment.
• Eligible to participate in EU-funded BlueOcean programme.
• Must not have resided or carried out main activity in the UK for more than 12 months in the 36 months before recruitment.
• At recruitment you must not have been awarded your doctorate.

Responsibilities

• Develop robotic monitoring and data processing methods for seafloor environments.
• Validate methods using simulations and existing Smarty200 AUV datasets.
• Collaborate with Ocean Perception group and field campaigns.
• Contribute to multidisciplinary training within the BlueOcean network.

Skills

Robotic localisation

High-resolution mapping

Machine learning

Probabilistic modelling

Education

PhD candidate status

Tools

Smarty200 AUV

Deep-water testing tank

Job description

Organisation/Company University of Southampton Research Field Engineering » Maritime engineering Computer science » 3 D modelling Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 31 Oct 2026 - 23:59 (Europe/London) Country United Kingdom Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Horizon Europe (other) Is the Job related to staff position within a Research Infrastructure? No

Offer Description

This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large spatial scales.

Motivation:Understanding how the seafloor evolves is critical for environmental monitoring and subsea infrastructure inspection. Natural processes and human activities drive changes over time, yet detecting these reliably remains challenging. Improved methods could enable early identification of risks to ecosystems and infrastructure, while providing quantitative evidence to support effective intervention and adaptive management.

Challenges:Documenting change in GNSS-denied subsea environments presents significant challenges. While changes occur over large spatial scales, change is often gradual, meaning that between seasonal or yearly deployments, the magnitude of change at any point on the seafloor remains below to the detection limit of even high-resolution mapping sensors. In addition, recognising and aligning scenes across repeated surveys is difficult due to navigation drift, evolving scene structure, and sensitivity to environmental conditions.

• How can evolving seafloor scenes be consistently recognised and spatially aligned across repeated subsea surveys in GNSS-denied environments?
• How can small seafloor changes be reliably detected when they are comparable to sensor noise?
• How can full-field uncertainty be modelled and propagated to support large-scale change analysis?

Approach:You will combine advanced robotic localisation and high-resolution mapping methods with advanced machine learning feature detection to enable evolving subsea scenes to be robustly aligned across repeat surveys. You will develop probabilistic models to detect subtle changes under noise and uncertainty. Your work will be validated using simulation, existing datasets from the University of Southampton’s Smarty200 AUV, and new data collected during field campaigns with the Ocean Perception group. Controlled experiments will also be conducted in the Maritime Robotics and Instrumentation Laboratory and its dedicated 8x8x6m deep-water tank.

Training and Environment:You will be part of the EU-funded BlueOcean Marie Skłodowska-Curie Doctoral Network, working alongside 13 PhD researchers across leading European institutions. The programme provides interdisciplinary training in robotics, sensing, and AI for marine monitoring, as well as access to internationally recognised experts and industry partners. You will also undertake up to two three-month secondments with organisations including CNR (Italy) and Voyis Imaging (Canada).

£43,994 to £47,279 Per annum, subject to bi-annual review due to exchange rate

The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.

The candidate:

- must not have a doctoral degree at the date of their recruitment

- can be of any nationality

- must not have resided or carried out their main activity (work, studies, etc.) in the UK for more than 12 months in the 36 months immediately before their recruitment date.

- At the time of recruitment (i.e. first date of employment), you must not have resided or carried out your main activity (work, studies, etc…) in the UK for more than 12 months in the 3 years immediately prior to recruitment under this project. Compulsory national service and/or short stays such as holidays are not taken into account. At the time of recruitment, you must not yet have been awarded your doctorate