英国肯特大学博士后职位---机器学习

英国肯特大学博士后职位---机器学习

Machine Learning Research Associate

University of Kent

Description

We are seeking a PhD graduate (or close to completion, or with equivalent experience and qualifications) as a Machine Learning Research Associate. The Associate will be responsible for the development and integration of machine learning models which match candidates to roles with HR GO's clients; leveraging the millions of datapoints collected by HR GO to embed within HR GO's systems ethical and transparent scoring, so that candidates can understand their progress towards and likelihood of achieving their next job.

This KTP project will mainly focus on developing a Machine Learning model which will power the job matching and recommendation engine within HR GO's ‘Candidate Account' web application. The model will be designed and implemented so that it can be used by multiple areas of the HR GO business.

This is a unique opportunity to work at HR GO and to engage with significant technical and commercial challenges. HR GO operates in the Staffing Industry and their revenue generating activities are the placing of candidates into temporary or permanent employment. In addition to placing candidates, HR GO provides both candidates and clients with online platforms to support their work. These may include facilities to manage timesheets, management information, onboarding, checking billing information, and ordering.

Please note that the Associate will be based at HR GO's premises in Ashford , being embedded in the HR GO Labs R&D function, and will work closely with the support and guidance of Dr Anna Jordanous and Dr Daniel Soria from the School of Computing, University of Kent. At the end of the fixed term contract, and upon successful completion of the project, there is a possibility that the role could become a permanent full-time position.

As a Machine Learning Research Associate you will:

  score candidates' suitability for jobs using HR GO data and make job recommendations to candidates based on their suitability

  accelerate and enrich the feedback loop between candidates and employers

  incorporate relevant contextual time series data collected by HR GO, for example, on attendance, shift duration, tenure, earnings, sickness, holiday etc. to further train models

  ensure that the rich data collected by HR GO is used ethically, responsibly and in compliance with the rights of the data subjects (GDPR and otherwise)

  write scientific papers associated with the work for publication in peer reviewed scientific journals

  Training HR GO's team members on the new systems and models developed during the project

To be successful in this role you will:

  have a PhD (or close to completion) in an area relevant to Computer Science, Machine Learning, Data Science, Artificial Intelligence or closely related disciplines

  have a BSc in Computer Science, Software or Electronic Engineering (or similar) with at least an upper second class 2:1 classification

  have experience of using techniques and frameworks for machine learning, data storage and data analytics

  have experience in conducting bibliographic research and writing reports

  be familiar with the agile methodology of system development processes and with using version control mechanisms to keep track of software development programmes

  be familiar with programming languages (preferably Python) and be familiar with techniques and frameworks for data storage, machine learning and/or data analytics (e.g., SciKit-Learn, Pandas)

We particularly welcome applications from female and black, Asian and minority ethnic candidates as they are under-represented at this level in this area