Machine Learning Engineer - (KTP Associate)

This is an exciting opportunity to work in a collaborative partnership between the University of the West of England (UWE) and partnership company under the UK Government sponsored Knowledge Transfer Partnership (KTP) programme. The position is a 36-month full-time fixed term contract, which includes management and business skills training provided by the national KTP programme and a further £2k per annum dedicated training budget tailored towards your personal development.

With specialist support from the academic team at UWE Bristol, you will lead on a 36-month project to establish a centre of excellence focused on designing products / solutions that address society's need for effective, compassionate, and forward-thinking care. Leveraging innovative technology to reduce injuries resulting from falls and other negative incidents for vulnerable individuals in social and health care settings. The project's primary objective is to develop a novel fall detection solution using camera technologies and cutting-edge AI, machine vision and machine learning techniques.

UWE Bristol along with the partnership company, celebrate diversity and seek talented people from all backgrounds to join us in a stimulating and supportive environment. We particularly encourage applications from Black, Asian, Multiple Heritage, or Other Minority Ethnic and underrepresented candidates, to ensure the strongest application pool possible. We promote equal opportunities and welcome applications from all suitably qualified candidates, regardless of race, gender, disability, religion/belief, sexual orientation, or age. Where necessary, adjustments can be made to attend interviews or carry out the role if successful.

Essential skills required:

• Strong knowledge and experience in machine learning (including deep learning such as convolutional neural networks), specifically in feature extraction, model development and evaluation.
• Proficiency in computer vision principles, image processing techniques, object detection, and camera technologies.
• Proficiency in at least one programming language commonly used in machine learning, such as Python, MATLAB, and C/C++.
• Robust data handling skills, including data collection, cleaning, preprocessing, and annotation.
• Strong problem-solving skills and critical thinking.
• Effective communication skills for collaborating with interdisciplinary teams, presenting research findings, and engaging stakeholders. Capable of conveying technical concepts to both technical and non-technical audiences.
• Adaptability to work at different venues and collaborate with a diverse team.
  
  
  

Desirable skills required:

• A PhD qualification or equivalent work experience in a related field.
• Experience in software development, version control, 3D imaging and collaborative coding practices.
• A willingness to work with hardware, such as Raspberry Pi, 3D cameras and accessories.
• Familiarity with assisted living concepts, terminologies, and data. Understanding clinical and social care workflows, patient privacy regulations and healthcare standards.
• Awareness of privacy regulations, ethical and safety considerations, security protocols.
  
  
  

Qualifications required:

Minimum 2.1 or masters in a Computing subject

Commutable within the Dorset/Hampshire region

Salary: £34k - £38k dependant on experience.

Interested candidates are strongly advised to contact Mel Smith to discuss the project along with any questions you have. E-mail: Melvyn.Smith@uwe.ac.uk

Any candidates wishing to apply who are subsequently appointed to this role without current Right to Work in the UK can be supported to obtain the Global Talent Visa (Endorsed Funder). This will involve a self-application which is a two stage process and we recommend you read the information about each stage on the following links: https://www.gov.uk/global-talent-researcher-academic/uk-research-innovation-endorsement

You may also wish to explore other visa options which you are eligible for which will allow you to work in the UK.

Please note that UWE does not cover any visa or health surcharge costs.