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Research Assistant/Associate in Deep Neural Networks for Real-Time Spectroscopic Analysis

Requisition ID:  19381
Location: 

Newcastle, GB

Contract Type:  Fixed Term
Working Pattern:  Full Time
Posted Date:  28-Apr-2022

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

 

We understand how important the full employment package is to our colleagues at Newcastle University and we are committed to providing a great range of benefits and discounts for all.  You can learn more about what is available here on our Benefits Website page.

 

Newcastle is an inclusive global University community where everyone is treated with dignity and respect.  As a University of Sanctuary, we aim to provide a welcoming place of safety for all, offering opportunities to people fleeing violence and persecution.

 

Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains colleagues from all sectors of society.  We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the communities 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.

 

Salary:

Research Assistant: £28,756 to £30,497 per annum

Research Associate: £31,406 to £36,382 per annum

 

Closing Date: 9 June 2022

 

The Role


We are looking to appoint a Research Associate in Deep Neural Networks for Real-Time Spectrospic Analysis. Based in Chemistry at Newcastle University, you will develop and use supervised machine learning/deep learning algorithms to transform the analysis of X-ray spectroscopy by developing and using easy-to-use, computationally inexpensive, and accessible tools for the fast and automated analysis of X-ray spectroscopy. This builds upon recent proof-of-concept work we have performed, e.g. paper1 and paper2.

 

You will have an undergraduate degree in a relevant science subject, preferably chemistry, physics or computer science; a PhD in computer science, theoretical or computational chemistry or a related discipline (candidates who have submitted their thesis will be considered).  You will also have expertise in calculating spectroscopic observables or implementing deep learning algorithms as well as experience with a computer programming language, preferably Python.

 

We would welcome requests for flexible working and depending on the needs of the role, blended working opportunities to work remotely as well as on-campus may be considered. Opportunities will be discussed should you be invited to interview.

 

As part of our commitment to career development for research colleagues, the University has developed 3 levels of research role profiles.  These profiles set out firstly the generic competencies and responsibilities expected of role holders at each level and secondly the general qualifications and experiences needed for entry at a particular level.

 

Information about the group can be found here.

 

Please provide evidence of how you meet the essential criteria required for the role outlined in ‘The Person’ by uploading a letter of application along with your Curriculum Vitae (CV)

 

For informal enquiries, please contact Thomas Penfold at tom.penfold@ncl.ac.uk


Key Accountabilities

  • Develop XANESNET Deep Neural Network for predicting X-ray spectra
  • Set up and develop accurate training and testing datasets
  • Analysis of results obtained
  • Coordinate the day-to-day running of the project including administration and organisation of meetings etc 
  • Interact with experimental collaborators
  • To implement other project deliverables as identified by the PI
  • Writing of scientific papers
  • Contribution to grant writing
  • Oral presentation at meetings

 

The Person 

 

Knowledge, Skills and Experience 

  • Expertise in calculating spectroscopic observables or implementing deep learning algorithms
  • Experience with a computer programming language, preferably Python.
  • Demonstratable experience of presenting research to both academic and lay audiences
  • Experience of producing academic publications
  • Practical skills in computational chemistry
  • Record keeping and data analysis
  • Excellent oral communication and writing skills

Desirable

  • Expertise in code development

 

Attributes and Behaviour

  • Well organised, with excellent time management
  • Innovative and flexible in approach
  • Strong team-working ethos
  • Ability to work independently and as part of a multidisciplinary team
  • Ability to work flexibly
  • Excellent planning, organisational skills and communication skills (both written and oral)
  • Professional approach with a commitment to equality, diversity, dignity, and respect in the workplace

Desirable

  • Publication of work in peer-reviewed journals with evidence of a developing research track record
  • Supervision of students (PhD, MSc, BSc)

 

Qualifications

  • Bachelor’s degree (or equivalent) in a relevant science subject – preferably chemistry, physics, or computer science
  • A PhD in the area of computer science, theoretical or computational chemistry or a related discipline (candidates who have submitted their thesis will be considered) 
     

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.

Requisition ID: 19381