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Job details
Job details
Job reference
19/107294
Date posted
07/03/2019
Application closing date
29/04/2019
Salary
£33,199 to £50,132 per annum
Job category/type
Academic
Attachments
Blank
Lecturer/Reader in Foundations of Data Science
Job description
Queen's University Belfast is one of the leading universities in the UK and Ireland, with a distinguished heritage and history. With over 24,000 students, 3,700 staff and an annual turnover of some GBP 300m, Queen's University Belfast plays a unique leadership role in Northern Ireland. As a member of the Russell Group of UK research-intensive universities,
Queen's University Belfast combines excellence in research and education with a student centred ethos.
As part of a major investment in Mathematical Sciences at Queen's University Belfast, applications are invited for the above post, to be held jointly between the School of Mathematics and Physics and the Institue of Electronics, Communication and Information Technology, to start as soon as practically feasible.
The successful candidate will join a dynamic research environment in a supportive and collegial setting at an exciting time, to develop the Foundations in Data Science and enhance mathematics education at Queen's University Belfast.
The successful candidate will demonstrate outstanding ability and potential. They will be research-driven and willing to play a decisive role in the Foundations of Data Science research at Queen's University Belfast, in collaboration with academics within the University and beyond. Successful candidates will be REF returnable within Mathematical Sciences and eligible to become Associate Members of the Institute of Electronics, Communication and Information Technology (ECIT) at Queen's University Belfast. Preference may be given to candidates specialising in Machine Learning, Combinatorial Optimisation and Applied Graph Theory, but strong candidates from all foundational fields of Data Sciences will be considered and are encouraged to apply.
For informal enquiries, please contact Professor Adele Marshall at
a.h.marshall@qub.ac.uk
Candidate Information - Reader
Candidate Information - Lecturer
About the School
Further information for international applicants
Note to EEA applicants on Brexit
Job title
Lecturer/Reader in Foundations of Data Science
Job reference
19/107294
Date posted
07/03/2019
Application closing date
29/04/2019
Salary
£33,199 to £50,132 per annum
Job category/type
Academic
Attachments
Blank
Job description
Queen's University Belfast is one of the leading universities in the UK and Ireland, with a distinguished heritage and history. With over 24,000 students, 3,700 staff and an annual turnover of some GBP 300m, Queen's University Belfast plays a unique leadership role in Northern Ireland. As a member of the Russell Group of UK research-intensive universities,
Queen's University Belfast combines excellence in research and education with a student centred ethos.
As part of a major investment in Mathematical Sciences at Queen's University Belfast, applications are invited for the above post, to be held jointly between the School of Mathematics and Physics and the Institue of Electronics, Communication and Information Technology, to start as soon as practically feasible.
The successful candidate will join a dynamic research environment in a supportive and collegial setting at an exciting time, to develop the Foundations in Data Science and enhance mathematics education at Queen's University Belfast.
The successful candidate will demonstrate outstanding ability and potential. They will be research-driven and willing to play a decisive role in the Foundations of Data Science research at Queen's University Belfast, in collaboration with academics within the University and beyond. Successful candidates will be REF returnable within Mathematical Sciences and eligible to become Associate Members of the Institute of Electronics, Communication and Information Technology (ECIT) at Queen's University Belfast. Preference may be given to candidates specialising in Machine Learning, Combinatorial Optimisation and Applied Graph Theory, but strong candidates from all foundational fields of Data Sciences will be considered and are encouraged to apply.
For informal enquiries, please contact Professor Adele Marshall at
a.h.marshall@qub.ac.uk
Candidate Information - Reader
Candidate Information - Lecturer
About the School
Further information for international applicants
Note to EEA applicants on Brexit