About Me

Showing posts with label PhD. Show all posts
Showing posts with label PhD. Show all posts

Thursday, January 23, 2014

NZ to AUS - Experiences from an academic

John Grundy:
Reasons for moving to AUS:
  • Was professionally happy in NZ; personally not so. Was the best time to be headhunted.
  • Opportunities for the children.
  • Opportunity to improve financially.
  • New place to live.
  • More focus on the research.
  • Tip: Get Australian Permanent Residency.

Australian way:
  • AUS richer than NZ.
  • More bureaucratic.
  • Steadily reducing Government funding (nothing new).
  • Government decides the student fees.
  • Recently changed to a "bums on seats" funding approach.
  • Competition for grants becoming more intense.
  • Universities may have multiple campuses overseas.
  • Feeder colleges (supplies new students to the University).
  • Deals with TAFEs, private providers, and feeders.
  • More unionised staff.
  • Superannuation is better. 17% employer, 8% employee.
  • Can salary package superannuation with cars, house, etc.
  • Salary levels about the same as in NZ (at the same currency?). Professors have a fixed salary of $160k.
  • Higher tax in AUS. 46% for the top earners.
  • Have to pay levies (e.g., flood levies)

Swinburne University:
  • Workload-model driven.
  • Some rank-based (e.g., prof -> tutor) research loadings.
  • A lot of time spent arguing about workloads
  • More diverse range of students.
  • Commericalisation not a big focus.
  • Common to have industrial-based learning.
  • Increasing number of students with mental health challenges.
  • Nomenclature of courses is different.

Funding:
  • Discovery projects:
    • Like the Marsden Fund.
    • 15-20% success rate.
    • 90-100 page proposals.
    • Does not cover overhead costs.
    • No salary - University donates staff time to the grant (Cost is recovered through teaching).
  • Linkage projects:
    • Like the Ministry of Business, Innovation, and Employment grants.
    • Australian industrial partner needed.
  • Excellence in Research for Australia:
    • Like the PbRF scheme.
    • Counts publications, grant income, etc.
    • Number crunching.
    • Central data collection.
    • Magic number generated only useful for bragging rights.
    • Quality of papers irrelevant?

My impression:
  • John has held leadership positions at UoA and now at SUT, and was able to convey the differences of both Universities and countries.
  • Since a large portion of the audience was UoA staff members who have worked with John, it felt like a personal and frank discussion (some anecdotes I could not pick up on because I didn't have the backstory).
  • The research/academic profession/environment of AUS is similar to NZ. Although, AUS is more bureaucratic and has a different work culture that is workload driven (not necessarily bad).
  • Everyone has to assess their own personal situation before changing jobs or moving to another country. It seemed like John was in a position where he needed a change and was headhunted at the right time and seems to be enjoying it (got his Australian Residency approved).
  • Previously, the main drawcard to working in Australia was the relatively higher pay. However, since the significant rise in the NZ dollar, this advantage is diminishing. This means the cost of living is not that much different between AUS and NZ.

Monday, December 16, 2013

STRATUS: Is there a future for emerging researchers in NZ? Surviving the postdoc apocalypse

Postdocalypse:
  • Science Exchange: Place to outsource scientific experiments. A way for labs to get funding for the work they like doing.
  • PhD can set you up for startups: Working on something useful, working on data, hardworking, passion.
  • Highly unlikely that postdocs end up being in a long term academic career.
  • Observation: Most researchers are old. Are we in prime position to replace them when they retire?
  • Industry and academic research being disconnected is the wrong mindset. Both tries to answer questions. Just don't lose your skills.
  • Learning to write grants is important!
  • UniServices can give the opportunity for a staff member to pause their teaching for a year and pursue their startup.
  • Overseas positions are good for character development.
  • Use your network to secure your postdoc.
  • Use the postdoc to learn what you want to do and what you don't want to do.
  • Be open minded and look beyond your mentors (e.g., lecturers, colleagues, etc).
  • Might need to step down to step up (in the ranks, pay, etc).
  • Your PhD should have trained you to plan a few years in advance. Periodically evaluate your goals.
  • Money is not why you want to be in research.
  • Tell your story positively.

Friday, February 26, 2010

Self-Sabotage

Patterns of behaviour
  • Overcommitting
  • Never saying no
  • Getting distracted
  • Perfectionism (measuring against)

Impostures syndrome
  • One step away from being found out as a fraud
  • Keep being an impostor
  • Others are also impostors

Saying no
  • Automatic Negative Thoughts (ANTs)
  • More Accurate Thoughts (MATHs)
  • ANTs ... and so ... MATHs

It's the thought that counts
  • Depends what you do with the thoughts.
  • Event -> Beliefs (intervening probabilities) -> Feelings

Twisted thinking (wrong conclusions -> wrong actions)
  • All or nothing
  • Over generalisation
  • Mental filter
  • Discounting the positives
  • Jumping to conclusions
  • Magnification
  • Emotional reasoning (feelings as facts)
  • Shoulds (assuming how things should be)
  • Labelling
  • Personalisation and blame

Procrastination
  • Avoidance strategies
  • Action -> Motivation -> Action -> More action
  • Break into smaller pieces
  • Procrastinators: Leaders of Tomorrow
Time management
  • Velcro fingers
  • The three D's
    • Do it
    • Diarise
    • Ditch it
  • Pareto principle (80/20)
    • 20% of the work leads to 80% of the output
Circles of influence
  • Core: Can control
  • Inner circle: Can influence
  • Outer circle: Can't control

Writing is not recording, it is thinking

Tuesday, October 27, 2009

Writing for academic publication

Gina Wisker

Why publish:
  • Finish PhD
  • Confidence in writing skills
  • Stop head spinning
  • Connecting with community
  • Sharing your research
  • People need to know your idea
  • Get feedback
  • Peer reviewed
What is stopping you:
  • Lack of confidence
  • Discourse
  • Not ready or fully developed thoughts
  • Fulfilling other obligations
  • Being a perfectionist
What helps you:
  • Deadlines with consequences
  • Presentation to colleges - views - ideas
  • Reading others' work
  • People supporting you for the effort
  • Teaching in anyway - coherent communication
What is appropriate to write and publish now?
  • Initial results and PhD direction
What you have been working on?
  • Getting familiar with tools to develop on top.
Who are you doing it for?
  • Supervisor: So they know I'm on track
  • Myself: Marks the first start of my PhD research
  • Community: Thoughts and feedback
Main issues to explore
Theories to use
Research to be done
What's done already by me?
Someone else
Outlet

Momentum

Calls to papers
What do the publishers like?
What do the editors like?

How does it contribute? What does it contribute? Why does this matter?

Publication / Conference
  • Publications are shorter
  • Conferences written in speech
  • Catch the butterflies in the conference and write them in the publication

Thursday, September 24, 2009

A refined sensor-ability: Applying process algebra to sensor network analysis

Allan McInnes

Communicating Sequential Processes (CSP): mutually consistent denotationally; operationally; and algebraic semantics.

Refinement can provide verification.

Node modeling. Example node:
  • TinyOS: programmed in nesC; component-based; Event driven.
  • TinyOS concurrency: Interrupts (asynchronous) and Task scheduling (synchronous). Task scheduling done with a FIFO queue.
  • Model executed on FDR2.

Network modeling:
  • Time Flooding Synchronization protocol: same time base (only says all nodes will have the same time, whatever it is).
  • Model maxed out at seven nodes.

Further refinements:
  • Network level models against node models. High -> Low level.
  • Check fault tolerance in a network.

Tuesday, August 11, 2009

Physiome

Computer readable format for representing biological models.

  • SBML
  • SBO
  • CellML
  • SBGN
  • insilicoML
  • MML
  • VCML

SBML

  • Declarative not procedural
  • Level 3 will support composition of modules

CML
  • Explicit mathematical modeling.
  • Meta data provides context. Simulation and graphing meta data. Application specific annotations.

MIRIAM

  • Proposed guidelines for annotation and curation of quantitative models.
  • Tuples: {data item} {optional qualifier} {entity qualifier}

MIASE and SED-OM and SED-ML

  • Minimum information required to replicate a simulation.

SBGN

  • Three languages: Process diagram; Activity flow diagram; Entity relationship diagram.

Physiome model description

  • Software agnostic description of the model.
  • Encoding standards.
  • Annotation.
  • Describe simulation experiments.
  • Describe simulation experiments.
  • Post processing.

Thursday, July 30, 2009

eResearch in New Zealand: Overview and Prospect

Seminar Notes:
  • Complexity of data, findings, ideas continually increasing.
  • Memex (Bush, 1946): external memory for storage/artefacts/experiments.
  • Accessibility: Equipment/computation/resources.
  • Complexity: Between disciplines.
  • Repeatability: Data, models.
  • Collaboration: Virtual presence.
  • Be able to use resources without knowing/no distinction.
  • Centralising data/sharing via the internet.

Thursday, July 23, 2009

The role of Industry and Universities in developing successful technology Industries

Tony's involvement:
  • Governance, Strategy building, Innovation management, Commercialisation of technology, Business growth.
  • Phitek, Senztek, Auckland UniServices, Auckland materials accelerator, FRST, Vesper Marine, BEP Marine, SiFE.
Universities:
  • Driven by knowledge, not financial success.
  • Science led research has long lead times to completion (esp biotech).
  • Little knowledge of market and competition.
  • Commercialising research:
    • validates the quality and relevance of the research.
    • builds status.
Companies seldom engage in fundamental research.

University technology transfer companies:
Good to go to the company's CEO and build a relationship there.

Good entrepreneurs delegating work to others. Bad entrepreneurs do all the work themselves.

Catch-22 with patent protection: Have to wait for patent to come through before product/service can be released; once you have the patent you need to be prepared to fight infringements - can be a stumbling block for start-ups since cash is limited.

If there's one idea, there must be another that goes with it?

Tuesday, March 3, 2009

Postgraduate place, medical, supervisor problems, wave, pgsa,

Postgraduate place, medical, supervisor problems, wave, pgsa,

The transition from taught learning to research:
Very careful speaker. You're now the person defining the question and answering it as well. 50% drop out rate by 4th year: reasons are more than just academic reasons. Pedantic work.

Make an original contribution, international standards, demonstrate knowledge of literature, satisfactory in its methodology.

Punctuation festival. Decisions. Self audit.


Theory

Assumptions are important. Perceptions can see through changing assumptions. Empirical for objectivity; connect facts together to form the truth. Exegentic for collecting recounts to form the truth. Qualitative for collecting subjectives to form the truth. Research approach.

If you were to cross the road and have to take note of all the stimuli around you, you would be uncapavle of crossing the road. Must filter out things but then you are limiting yourself in scope.

Language is a metaphor.