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Machine Learning Engineer (KTP Associate) - 2 year fixed term

My First Five Years -

Full-time (Permanent)
£30,000 - £33,000
Published on
15 June 2022
Deadline
10 July 2022

The role:

An exciting opportunity has become available to work full time on a 2-year Knowledge Transfer Partnership (KTP) to develop a novel Machine Learning and Artificial Intelligence capability to determine how such approaches can be applied to develop predictive capabilities related to child development.

Employed and supported by an academic team from the University, you will be based at the company's premises in Didsbury.

Company information:

My First Five Years is an educational platform and mobile app offering personalised guidance to parents during the formative (first five) years of their child's life, creating a safe and supportive learning space for parents to support their child's unique physical, cognitive and emotional development.

To find out more about My First Five Years, go to www.mffy.com

Qualification we require:

MSc or PhD in Computer Science, Artificial Intelligence (AI), Statistics, Mathematics, Data Science, or related discipline. Candidates with a first class (Hons) degree in a relevant subject, such as Data Science or Computer Science with evidence of conducting a machine learning (or AI) project will be considered.

Application requirements:

  • Ability to understand and implement algorithms and data science pipelines together with full documentation to allow reproducible outcomes, for example Python and its Data Science ecosystem, e.g., NumPy, pandas, Matplotlib, scikitlearn, PyTorch, Keras.
  • Ability to perform software design, implementation, testing and version control (e.g., Git and GitHub) using sound software engineering principles and practices, together with strong programming skills and fully conversant in Object Oriented Programming (e.g,. Java, C#, etc) and Data Structures.
  • Experience in selection, implementation and application of suitable machine learning algorithms, for optimisation (e.g. Genetic Algorithms, Particle Swarm) or clustering for a specific problem domain.
  • Most stages of data science pipelines, including data extraction, integration, cleaning, normalisation, model building with inferential statistics and machine learning, and data visualisation.

The successful candidate will:

  • Possess good oral and written communication skills with the ability to lead a project from the technical/scientific perspective and to produce research outputs such as academic papers publishable at top venues.
  • Be capable of working collaboratively in a small team environment.
  • Be able to work independently, make decisions and manage personal workload.
  • Have a passion for discovering knowledge from data and the ability to tell stories from data.
  • Be capable of communicating complex concepts in a clear manner to a wide-ranging audience.
  • Be keen to work in a future focused environment that is rapidly evolving.

Benefits:

  • £2,000 per year to spend on personal training;
  • attendance at two residential managerial workshops (each of one week's duration);
  • opportunity to register on a higher degree (at a reduced cost);
  • opportunity of a permanent position with the company; 70% of host companies make a permanent job offer to their Associate at the end of the project.

For an informal discussion, please contact Professor Keeley Crockett k.crockett@mmu.ac.uk or Dr David McLean d.mclean@mmu.ac.uk

Apply by submitting a CV and covering letter detailing how you meet the criteria for the role.

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