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James Hind

Lecturer/Senior Lecturer

School of Science & Technology

Staff Group(s)
Physics and Mathematics

Role

Dr James Hind is the Admissions Tutor for the Maths team and works on outreach, employability and placement projects as well as being a lecturer in Statistics.

Career overview

Dr Hind was previously a Research Fellow in Bioinformatics at the John Van Geest Cancer Research Centre.

Research areas

Dr Hind's research interests include Liquid Crystal Physics, Bioinformatics, Mathematics pedagogy, eLearning and data analysis.

Opportunities to carry out postgraduate research towards an MPhil/PhD in the School of Science and Technology exist and further information may be obtained from the the NTU Graduate School.

External activity

  • Invited lecturer for Manchester Metropolitan University (2013, 2014)
  • Big Bang Fair contributor (2014)

Sponsors and collaborators

Dr Hind has received two grants from HESTEM to look at pedagogic and student employability issues:

  • Mathematics progression project. J Hind, HESTEM, (2010), £1,250. Mathematics Progression was a small project designed to encourage A-level students to take Mathematics at degree level and to encourage Mathematics students at degree level to consider teaching Mathematics as a career. This has evolved into wider outreach activities within the local area and continued student involvement through the final year project system.
  • Graduate transitions in Mathematics. J Hind, HESTEM, (2011), £21,000. This was a project designed to support graduates in applying for graduate level positions. It involved the creation of a graduate survival guide and a modified assessment activity in the Problem Solving module specifically tied to the skills and abilities required by employers of mathematics graduates.

Publications

Publications

For full list click 'Go to James Hind's publications' link above.

See all of James Hind's publications...

Press expertise

  • Liquid crystals and liquid crystal displays
  • Machine learning and artificial neural networks
  • Snow – its maths, physics and chemistry
  • Statistics
  • Data analysis
  • Big data