Mathematics and Statistics Postgraduate Recruitment

• for Taught Masters there were statistics work placements/internships. Did this for the first time last year - 3-5 got work out of these placements but this is nothing we could promise for the future
• paid and unpaid projects with companies - student project was sponsored by NIWA
• Internships
  • School does all the organisation of these as it is a requirement of the Masters of Applied Statistics qualification
  • the students have a choice about where they go
  • The School is planning to add pages to their website about internships and projects.

• MSc only - 1 year coursework and 1 year thesis. Options include:
• Subjects
  • Data Science
  • Applied Mathematics
• Math thesis haven't been linked to industry but this could happen in the future.

• Thesis may be linked to existing grants staff has.
• Can also choose their own topic

• Masters scholarship
• If it is linked a funded project they may be able to go to conference
• PhD student may get paid by funded projects e.g. Marsden grants
• private company may supply scholarships e.g. NIWA

• UG wanting to do a thesis > PhD or Masters
• UG wanting to do coursework > PG Dip, Masters, Honours
• At the moment they want to increase the number of students doing thesis, currently numbers are low. Coursework numbers are good.
• At 400 level the learning curve takes off steeply.
• PhD from taught masters - they can choose to do Masters part 2 and then do a PhD. If they were to go straight into a PhD they would need to be an exceptional student.
• Masters part 1 to PhD - they would need to be an exceptional student.
• it is hard to get students to choose the thesis as they can get jobs so why bother.
• easy to recruit international students into PhD and they get good quality students.

• to get work, they wouldn't get analysis work with just a UG degree.
• Their opportunities will be wider and their salaries higher.

• MAS
  • they have facebook page
  • very social with rest of cohort
  • course includes teamwork
  • have lab
• PhD
  • very close to staff
  • help with teaching - tutoring and occasional lecture
  • are integrated into school like a staff member
  • have a shared office
• MSc
  • have a shared office / 4 or 5 offices
• MSc taught
  • have a lab
  • locker
  • computer

In general

• every two weeks have events - seminars. Staff present and sometimes outside people if they have the budget to support this - generally from NZ or Aust. Overseas visitors may be included if they were here already for another reason.
• regularly have overseas academics visiting.

• 2017
  • offereing courses related to datascience at the UG level. The courses didn't exist in July but may now - worth checking.
  • this will allow them to align to taught masters in the future.
  • Data Science is Maths and Stats combined with Computer Science. Traditionally people have done either but not both, this helps bring it together. e.g. report on when people click on the link. To do this you need to answer the following questions:
    • how do you sotre this
    • how do you process/display
    • how to you analyse it - make sense of the information, find the important bits, make predictions