Research Assistant/Associate (Statistical Modeller) – ACHILLES - D196569R
 


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

Closing Date: 01 May 2019

We are seeking to support a talented and enthusiastic RA with experience in Bayesian statistical modelling or similar discipline to work pro-actively with a multi-university research consortium to learn new skills and bring state-of-the-art statistical modelling techniques to problems in data-centric engineering. You will conduct research with 2 main components:

1. Using Bayesian hierarchical modelling to develop network scale performance models by integrating geotechnical numerical models of asset condition and deterioration with available network data.

2. Using spatio-temporal modelling techniques to properly quantify and propagate uncertainty associated with missing data and future weather/climate.

You should have a PhD in Statistics, or a closely related discipline (awarded or nearing completion) with experience in computational Bayesian statistics, statistical modelling, and the production of high quality journal publications. Knowledge of hierarchical models, computer model emulation, and engineering applications is highly desirable.

You will be based in the School of Mathematics, Statistics and Physics, working on the EPSRC funded ACHILLES (Assessment, Costing and enHancement of long life Long Linear Assets) Programme.

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 full time, fixed term post available for the duration of 24 months.

Informal enquiries can be made to: Prof Darren Wilkinson: darren.wilkinson@newcastle.ac.uk  

Further information can be found on the following job weblinks:
https://research.ncl.ac.uk/achilles/
https://www.ncl.ac.uk/maths-physics/
https://www.staff.ncl.ac.uk/d.j.wilkinson/

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.

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: 01 May 2019

We are seeking to support a talented and enthusiastic RA with experience in Bayesian statistical modelling or similar discipline to work pro-actively with a multi-university research consortium to learn new skills and bring state-of-the-art statistical modelling techniques to problems in data-centric engineering. You will conduct research with 2 main components:

1. Using Bayesian hierarchical modelling to develop network scale performance models by integrating geotechnical numerical models of asset condition and deterioration with available network data.

2. Using spatio-temporal modelling techniques to properly quantify and propagate uncertainty associated with missing data and future weather/climate.

You should have a PhD in Statistics, or a closely related discipline (awarded or nearing completion) with experience in computational Bayesian statistics, statistical modelling, and the production of high quality journal publications. Knowledge of hierarchical models, computer model emulation, and engineering applications is highly desirable.

You will be based in the School of Mathematics, Statistics and Physics, working on the EPSRC funded ACHILLES (Assessment, Costing and enHancement of long life Long Linear Assets) Programme.

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 full time, fixed term post available for the duration of 24 months.

Informal enquiries can be made to: Prof Darren Wilkinson: darren.wilkinson@newcastle.ac.uk  

Further information can be found on the following job weblinks:
https://research.ncl.ac.uk/achilles/
https://www.ncl.ac.uk/maths-physics/
https://www.staff.ncl.ac.uk/d.j.wilkinson/

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.

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.