Postdoctoral Research Associate

Updated: 3 months ago
Location: Durham, ENGLAND

Postdoctoral Research Associate (
Job Number:
 22001399)
Department of Computer Science
Grade 7: - £35,333 - £42,155 per annum
Fixed Term - Full Time
Contract Duration: up to 18 months, start date dependant
Contracted Hours per Week: 35
Closing Date
: 14-Sep-2022, 6:59:00 PM 

Durham University
 

Durham University is one of the world's top universities with strengths across the Arts and Humanities, Sciences and Social Sciences. We are home to some of the most talented scholars and researchers from around the world who are tackling global issues and making a difference to people's lives.

 

The University sits in a beautiful historic city where it shares ownership of a UNESCO World Heritage Site with Durham Cathedral, the greatest Romanesque building in Western Europe. A collegiate University, Durham recruits outstanding students from across the world and offers an unmatched wider student experience.

 

Less than 3 hours north of London, and an hour and a half south of Edinburgh, County Durham is a region steeped in history and natural beauty. The Durham Dales, including the North Pennines Area of Outstanding Natural Beauty, are home to breathtaking scenery and attractions. Durham offers an excellent choice of city, suburban and rural residential locations. The University provides a range of benefits including pension and childcare benefits and the University’s Relocation Manager can assist with potential schooling requirements.

 

Durham University seeks to promote and maintain an inclusive and supportive environment for work and study that assists all members of our University community to reach their full potential. Diversity brings strength and we welcome applications from across the international, national and regional communities that we work with and serve.


 
The Department
 

The Computer Science Department is a UK Top 10 Department (Complete University Guide 2023). We are committed to high-quality teaching and research. The Department increased excellence in all research areas since the last research assessment exercise, moving six places up the ranking to the 20th position for REF 2021. We are proud of our emphasis on equality, diversity and inclusion and are working hard to make our department the no.1 University in the UK for women to study Computer Science.


 
The Role
 

Applications are invited for a Postdoctoral Research Associate to undertake research as directed by the investigator team of the EPSRC-funded Twenty20Insight project. The role's focus is to investigate and develop methods, tools and techniques to help build decision-making models for non-functional requirements trade-offs, based on techniques such as Partially Observable Decision Networks (POMDP) and Bayesian Neural Networks (BNN). These models will be further used for uncertainty reasoning and explanation/understanding of the decision-making. In particular, the post holder will investigate how techniques from the fields of Requirements Engineering, Software Engineering and Machine Learning (POMDP and BNN) may be combined. The aim is to help build models for supporting decision-making under uncertainty, considering trade-offs of non-functional requirements (NFR) for cases of dynamic adaptation. 


 
Responsibilities  :
  • To understand and convey material of a specialist or highly technical nature to the team or group of people through presentations and discussions that leads to the presentation of research papers in conferences and publications.
  • To prepare and deliver presentations on research outputs/activities to audiences which may include: research sponsors, academic and non-academic audiences.
  • To publish high quality outputs, including papers for submission to peer reviewed journals and papers for presentation at conferences and workshops under the direction of the Principal Investigator or Grant-holder.
  • To assist with the development of research objectives and proposals.
  • To conduct individual and collaborative research projects under the direction of the Principal Investigator or Grant-holder.
  • To work with the Principal Investigator or Grant-holder and other colleagues in the research group, as appropriate, to identify areas for research, develop new research methods and extend the research portfolio.
  • To deal with problems that may affect the achievement of research objectives and deadlines by discussing with the Principal Investigator or Grant-holder and offering creative or innovative solutions.
  • To liaise with research colleagues and make internal and external contacts to develop knowledge and understanding to form relationships for future research collaboration.
  • To plan and manage own research activity, research resources in collaboration with others and contribute to the planning of research projects.
  • To deliver training in research techniques/approaches to peers, visitors and students as appropriate.
  • To be involved in student supervision, as appropriate, and assist with the assessment of the knowledge of students.
  • To contribute to fostering a collegial and respectful working environment which is inclusive and welcoming and where everyone is treated fairly with dignity and respect.
  • To engage in wider citizenship to support the department and wider discipline.
  • To engage in continuing professional development by participation in the undergraduate or postgraduate teaching programmes or by membership of departmental committees, etc. and by attending relevant training and development courses.

 

This post is fixed term for up to 18 months dependant on start date. The funding is available from 01/10/2022 to 31/03/2024, when the EPSRC's funding for Twenty20Insight ends.

 

The post-holder is employed to work on research which will be led by another colleague. Whilst this means that the post-holder will not be carrying out independent research in their own right, the expectation is that they will contribute to the advancement of the project, through the development of their own research ideas/adaptation and development of research protocols.


 
Successful applicants will, ideally, be in post no later than 01/11/2022
 
How to Apply
 

For informal enquiries please contact Dr Nelly Becomo (nelly.bencomo@durham.ac.uk ).  All enquiries will be treated in the strictest confidence. 


 

We prefer to receive applications online via the Durham University Vacancies Site. https://www.dur.ac.uk/jobs/ . As part of the application process, you should provide details of 3 (preferably academic/research) referees and the details of your current line manager so that we may seek an employment reference.


 

Applications are particularly welcome from women and black and minority ethnic candidates, who are under-represented in academic posts in the University  .


 
What to Submit
 
All applicants are asked to submit:
  • A CV and covering letter which details your experience, strengths and potential in the requirements set out above.

 
Next Steps
 

The assessment for the post will include an interview and presentation. Shortlisted candidates will be invited for interview and assessment during September 2022.




The Requirements

Essential:

  • Qualifications
  • (Method of assessment: application form)

    • A PhD (or be close to submission) in Computer Science, Machine Learning, or a related subject.
  • Experience
  • (Method of assessment: application form, interview and presentation) 

    • Experience in applying Machine Learning and/or Bayesian Inference techniques in a Software Engineering context.
  • Skills
  • (Method of assessment: application form, interview and presentation) 

    • Ability to work across discipline boundaries.
    • Excellent interpersonal and communication skills: ability to communicate effectively with colleagues and stakeholders, verbally, textually, and via (physical, graphical or digital) models.

    Desirable:

  • Experience
  • (Method of assessment: application form, interview and presentation) 

    • Knowledge of Bayesian Neural Networks (BNN) and Bayesian inference and decision-making under uncertainty.
    • Experience of developing self-adaptive applications using Machine Learning (e.g. Bayesian Neural Networks (BNN), Partially Observable Markiv Decision Processes (POMDPs)).
    • Experience of designing applications for self-adaptive systems with decision-making under uncertainty.
    • Experience of applying Machine Learning techniques in a Software Engineering context.

     



    DBS Requirement: Not Applicable.
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