Machine Learning Software Engineer – UOD1381

Overview

The School of Science and Engineering has an international reputation for excellent teaching and topical research, particularly in addressing global challenges in energy, the environment, health care, technology, forensic science and infrastructure.

The Leverhulme Research Centre for Forensic Science is a 10 year £10 Million project with the remit to disrupt positively the current forensic science ecosystem. As a key appointment in the £10m Leverhulme Research Centre we are recruiting for an exceptional individual to join us as a Machine Learning Software Engineer within our team to work on innovative, inter-disciplinary research and engage in the development of accessible data sets, and the generation of novel machine learning solutions to comparison problems.

You will have a background in computational mathematics and/or software engineering preferably in Python and R, with a strong and demonstrable experience in AI/ML methods in the handling and modelling of complex data sets… including image analysis. You should have a proven track record of applying computational solutions to research problems including data curation, data cleaning, storage and retrieval, organising workflows and meeting deadlines.

Your priorities will include:
• Deliver individually, or in collaboration with others, software engineering solutions for use by the research team and the wider practitioner community including, but not limited to, the development of software and web/mobile based applications.
• Apply machine learning best practices to external and in-house data, including capturing and preparing data sets for analysis.
• Develop methodologies for the processing of a wide variety of data from advising on (or actual) data collection, preparation, triage, analysis and dissemination.
• Provide support and frontline trouble shooting and maintenance of existing and new software engineered assets including those which facilitate research outputs.
• Challenge and probe existing methodologies for pattern recognition related to forensic science data and undertake research to develop machine learning and deep learning-based improvements.

Who we’re looking for:
• MSc or PhD in a relevant subject or equivalent and demonstrated industry/operational experience.
• Evidence of expertise and experience in agile programming in a wide variety of software and programming languages such as SQL, MySQL, JavaScript, PHP, C++, Java, Python, R, R-shiny, ORM and use of the relevant ML libraries and Git version control.
• Demonstrable depth and breadth of knowledge of the practical application of AI/ML and deep learning to atypical data sets which might include feature extraction and comparison.
• Evidence of ability to produce outputs of quality and excellence.

We are one of the UK’s leading universities, internationally recognised for our expertise across a range of disciplines and research breakthroughs in multiple areas, including science, medicine and engineering, amongst many others. Our purpose is to transform lives, locally and globally, which we do as a community of staff (Professional Services and academic Schools), students and alumni. Professional Services directorates are key to delivering the University strategy and driving change across the University.

To further discuss the details of this post, informal inquires may be made to Professor Niamh NicDaeid (), LRCFS Director or Dr Roberto Puch-Solis () LRCFS Principal Investigator in Forensic Statistics.

To find out more about LRCFS please visit https://www.dundee.ac.uk/leverhulme

Company:

University of Dundee

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Academia, Machine Learning, NLP, Pattern Recognition, United Kingdom