Research Associate/Research Assistant - D171328R2
 

Salary: £27,831 - £29,515 per annum (PhD Submitted - Assistant Level)
            £30,395 - £39,610 per annum (PhD Awarded - Associate Level)

Closing Date: 19 April 2019

We are seeking to appoint a Research Associate/Assistant in Statistics to the project Streaming data modelling for real-time monitoring and forecasting. This project is funded by the Alan Turing Institute (the UK’s National Institute for Data Science and Artificial Intelligence) and will be led by a research team from Newcastle University who will develop an international leading capability for the (near) real-time analysis of streaming data. This project will offer the opportunity for collaboration with other Turing projects and researchers at Newcastle and elsewhere.

You will possess a PhD in Statistics or a closely related discipline (awarded or in submission); expertise in Bayesian inference and computationally intensive inferential methodology; track record of research in computational Bayesian statistics and developing efficient programs for statistical computing.

You will have excellent statistical computing skills, including familiarity with modern statistical tools and libraries; strong programming skills in R and an efficient compiled language like C/C++ or Java/Scala; excellent written and oral communication skills; effective time management skills.

Please be advised that due to the minimum salary threshold of £30,000 per annum imposed by the UKVI, this post may not qualify for University sponsorship under Tier 2 of the points based system.

The University holds a silver Athena SWAN award in recognition of our good employment practices for the advancement of gender equality.  The University also holds the HR Excellence in Research award for our work to support the career development of our researchers, and is a member of the Euraxess initiative supporting researchers in Europe.


This is a fixed term post for 24 months.

For informal enquiries contact Prof Darren Wilkinson (darren.wilkinson@ncl.ac.uk ) or Dr Andrew Golightly (andrew.golightly@ncl.ac.uk )

Further information can be found using the web links below:

• Prof Darren Wilkinson: http://www.staff.ncl.ac.uk/d.j.wilkinson
• Dr Andrew Golightly: http://www.ncl.ac.uk/maths/staff/profile/andrewgolightly  
• Dr Chris Oates: http://www.ncl.ac.uk/maths/staff/profile/chrisoates
• School of Mathematics, Statistics and Physics: http://www.ncl.ac.uk/maths-physics

Click here for further details

Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains staff from all sectors of society.  We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the community they represent.  We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices. 


Faculty/Services
Faculty of Science, Agriculture & Engineering
Unit
Mathematics, Statistics and Physics
Sub Unit
Mathematics and Statistics
Staff Category
Research
Contract Type
Fixed Term
Hours of Work
Full Time
Location
Newcastle upon Tyne
 
Salary: £27,831 - £29,515 per annum (PhD Submitted - Assistant Level)
            £30,395 - £39,610 per annum (PhD Awarded - Associate Level)

Closing Date: 19 April 2019

We are seeking to appoint a Research Associate/Assistant in Statistics to the project Streaming data modelling for real-time monitoring and forecasting. This project is funded by the Alan Turing Institute (the UK’s National Institute for Data Science and Artificial Intelligence) and will be led by a research team from Newcastle University who will develop an international leading capability for the (near) real-time analysis of streaming data. This project will offer the opportunity for collaboration with other Turing projects and researchers at Newcastle and elsewhere.

You will possess a PhD in Statistics or a closely related discipline (awarded or in submission); expertise in Bayesian inference and computationally intensive inferential methodology; track record of research in computational Bayesian statistics and developing efficient programs for statistical computing.

You will have excellent statistical computing skills, including familiarity with modern statistical tools and libraries; strong programming skills in R and an efficient compiled language like C/C++ or Java/Scala; excellent written and oral communication skills; effective time management skills.

Please be advised that due to the minimum salary threshold of £30,000 per annum imposed by the UKVI, this post may not qualify for University sponsorship under Tier 2 of the points based system.

The University holds a silver Athena SWAN award in recognition of our good employment practices for the advancement of gender equality.  The University also holds the HR Excellence in Research award for our work to support the career development of our researchers, and is a member of the Euraxess initiative supporting researchers in Europe.


This is a fixed term post for 24 months.

For informal enquiries contact Prof Darren Wilkinson (darren.wilkinson@ncl.ac.uk ) or Dr Andrew Golightly (andrew.golightly@ncl.ac.uk )

Further information can be found using the web links below:

• Prof Darren Wilkinson: http://www.staff.ncl.ac.uk/d.j.wilkinson
• Dr Andrew Golightly: http://www.ncl.ac.uk/maths/staff/profile/andrewgolightly  
• Dr Chris Oates: http://www.ncl.ac.uk/maths/staff/profile/chrisoates
• School of Mathematics, Statistics and Physics: http://www.ncl.ac.uk/maths-physics

Click here for further details

Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains staff from all sectors of society.  We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the community they represent.  We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices.