Research Assistant in Data Science

The Role

We are seeking a highly skilled and motivated Data scientist to join our team. The scientist will work on the development and implementation of machine learning models aimed at detecting urban drainage infrastructure components (such as stormwater drains, sewers, and manholes) from publicly available street-level images. 

The role will also involve developing models to identify obstructions, such as debris or blockages, within these systems to support real-time monitoring and flood risk mitigation efforts.

The post is based in the internationally leading Water Group in the School of Engineering but will work collaboratively with researchers from many other disciplinary backgrounds from Newcastle University, the Tyndall Centre for Climate Change Research. 

The post is available on a fixed term basis, for immediate start the post is funded for 6 months.

For further information on The School of Engineering please click . 

For further information surrounding this research please click . 

To apply, please complete an online application, upload a CV and a cover letter. Your cover letter should be a detailed supporting statement outlining why you are a good fit for the role. Please explain how you meet the essential criteria outlined below and evidence this with examples. 

For informal queries please contact Vassilis Glenis

Key Accountabilities

Design, develop, and implement machine learning models for the automated detection of drainage infrastructure from street-level images

Build models that identify debris and blockages in urban drainage systems.
Analyse and preprocess large datasets of street-level images for model training and validation
Collaborate with flood modelling and urban infrastructure teams to integrate ML outputs into broader flood risk assessment frameworks
Continuously evaluate model performance and improve its accuracy and efficiency
Document project progress, report results, and present findings to stakeholders
Stay up to date with the latest machine learning techniques and tools, particularly in the field of computer vision

The Person 

Knowledge, Skills and Experience 

Proven experience with machine learning model design and implementation, particularly in computer vision tasks (image classification, object detection)

Strong programming skills in Python, and familiarity with libraries such as TensorFlow, Keras, PyTorch, or similar
Experience working with large datasets and applying data preprocessing techniques (e.g., image augmentation, normalization)
Knowledge of urban drainage systems or civil infrastructure is a plus, but not required
Experience in analysing and identifying anomalies, such as blockages or debris in images, is highly desirable
Strong problem-solving skills and ability to work independently
Ability to communicate complex technical ideas effectively with non-technical stakeholders

Attributes and Behaviour

Excellent communication skills (written and verbal)

Excellent interpersonal skills to build trust with collaborating groups
Good planning, organisational and time management skills

Qualifications

A Bachelor’s or Master’s degree in a relevant subject e.g. Engineering, Maths, Computer Science

Newcastle University is a global University where everyone is treated with dignity and respect. As a University of Sanctuary, we aim to provide a welcoming place of safety for all, offering opportunities to people fleeing violence and persecution.

We are committed to being a fully inclusive university which actively recruits, supports and retains colleagues from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all of our employees and the communities they represent. We are proud to be an equal opportunities employer and encourage applications from individuals who can complement our existing teams, we believe that success is built on having teams whose backgrounds and experiences reflect the diversity of our university and student population.

At Newcastle University we hold a silver award in recognition of our good employment practices for the advancement of gender equality. We also hold a Bronze award in recognition of our work towards tackling race inequality in higher education REC. We are a employer and will offer an interview to disabled applicants who meet the essential criteria for the role as part of the offer and interview scheme.

In addition, we are a member of the Euraxess initiative supporting researchers in Europe. 

Requisition ID: 28272