Machine Learning Research Associate

KTP

Knowledge Transfer Partnerships (KTPs) are a unique UK-wide activity that help businesses to improve their competitiveness and productivity by making better use of the knowledge, technology and skills within universities, colleges and research organisations. Further information is available at: www.ktponline.org.uk

THE PROJECT

The University of Essex in partnership with IFE Global Logistics Ltd offers an exciting opportunity to a graduate with the relevant skills and knowledge to design a custom transport management system using advanced machine learning techniques and data science for process automation and accurate prediction of vessel arrival times in the context of sea freight forwarding. This post is fixed term for 33 months and is based at IFE Global Logistics’ offices in Basildon.

DUTIES OF THE POST

The duties of the post will include:

• Build and automate a Transport Management System (TMS).
• Develop Optical Character Recognition (OCR) for text recognition and document understanding automated TMS.
• Process and analyse text data.
• Use machine learning algorithms to predict vessel arrival time.
• Identify the different factors that affect arrival time.
• Transferring machine learning knowledge to other IFE employees.
• Managing a complex project with multiple stakeholders, monitoring and reporting on progress and ensuring objectives are met.
• Co-authoring articles in collaboration with academics at the University of Essex.
• Incorporating AI technologies into shipment tracking algorithms.
• The design, build, management and maintenance of relational database schemas.

These duties are a guide to the work that the post holder will initially be required to undertake. They may be changed from time to time to meet changing circumstances.

KEY REQUIREMENTS

• BSc in Computer Science, Artificial Intelligence, Data Science, Electronic Engineering or related discipline.
• MSc in Computer Science, Artificial Intelligence, Data Science, Electronic Engineering or equivalent industry experience.
• PhD in Computer Science, Artificial Intelligence, Data Science, Electronic Engineering, or equivalent industry experience.
• High level of knowledge and experience of computational /artificial intelligence.
• Experience of deploying and tuning classification and regression algorithms.
• Experience handling large and complex data.
• Knowledge and experience in deep learning and neural networks (e.g., Pytorch, Tensor Flow, Scikit-learn).
• Knowledge and experience in optimisation, modelling and algorithm development.
• Knowledge and experience in data visualisation.
• Java or Python programming.
• Ability to deploy a complex ML project within a commercial setting.
• Ability to contribute to the drafting academic papers.
• Ability to navigate a complex organisation, working across teams with a large number of stakeholders.
• An understanding of the need to balance academic and commercial outputs.
• Ability to communicate complex and technical concepts to a range of technical and non-technical stakeholders.
• Ability to work on own initiative and as a part of a team.
• Good command of written and spoken English.

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