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伦敦大学学院 (University College London，简称UCL），于1826年始建，位于英国伦敦，是一所世界著名的顶尖高等学府，为伦敦大学联盟创始院校，英国金三角名校，与剑桥大学、牛津大学、帝国理工、伦敦政经学院并称G5超级精英大学。

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This is an exciting opportunity for computer science postgraduates and postdocs to lead a project that will apply cutting edge research in data science in a brand new way to the recruitment industry.

With full support from computer science experts at UCL and the company partner, global Software as a Service provider Oleeo plc, the KTP Associate will develop an intelligent mathematical model that can identify the best candidate applications for a certain vacancy.

This will involve using advanced machine learning, recruitment dataset analysis and network science techniques to generate real impact in Oleeo’s fast-moving business environment.

Plus, the successful candidate will be part of the prestigious 40-year-old national Knowledge Transfer Partnership programme offering a dedicated professional development budget, a network of fellow Associates from many disciplines and training and mentoring opportunities.

Find out more about KTPs here: https://ktn-uk.co.uk/programmes/knowledge-transfer-partnerships.

The post is funded until 29th November 2021 in the first instance however there may be potential to continue with the company partner following the completion of the KTP project.

This role offers a springboard to a career in both industry and academia to or a visiting scholar and postdocs in Computer Science, Data Science, Machine Learning and related disciplines.

The successful candidate will get to apply their Python programming, machine learning, network science, mathematical and statistical analysis skills on a daily basis to a cutting edge data analysis and exploration project.

Strong communication skills, a collaborative attitude and good project management skills will ensure the KTP.

Associate fully enjoys the benefits of their unique position at the interface between industry and academia, including their close access to computer science experts from both.

Applicants should apply online. To access further details about the position and how to apply please click on the ‘Apply’ button above.

If you have any queries regarding the vacancy or the application process, please contact Jun Wang (Junwang@cs.ucl.ac.uk)

UCL Taking Action for Equality.