I'm thinking of transitioning from computational fluid dynamics research to doing experimental fluid stuff. How would you contrast the workflow and the big challenges between computational scientific work and experimental scientific work?

  • You may want to tweak the title to clarify how discipline specific your question is intended to be... I.e., is it only about fluid dynamics or is about some broader discipline. Jul 7, 2016 at 0:34
  • Its not intended to be discipline specific. Jul 7, 2016 at 0:52
  • The body of your question is very specific, yet your title is general. I feel like they should be aligned. So you're just as interested in moving from quantitative modelling in psychology to running social science experiments with human participants as you are in the context of say physics, chemistry, or biology? More broadly, surely the meaning of the word "experimental research" would vary widely between disciplines. Jul 7, 2016 at 1:46
  • Oh. I meant more "Hard science" computational vs experimental. Like computational chemistry to chemistry in a lab or computational biophysics to a biophysics wet lab or in my case computation fluids work to experimental fluids work. Jul 7, 2016 at 18:35

1 Answer 1


I, a Chemical engineer by paper and I recently made a big leap from desktop work - purely predictive modelling of process plants and systems, to experimental lab based work in the field of Biotechnology. Back to the world of pipettes, organic chemistry and filtration!

The experience I feel depends on whether you are going from computational modelling to quantitative experimental work in the natural science field ( like what I have experienced), or to qualitative (or even quantitative) in the social field. I have experienced both!

From laptop work to the biotech lab!

Challenges (I have faced):

  • It is difficult to get from an experimental planning to execution stage in the labs (often due to over researching online)
  • There is little evidence of your work ( it is all sitting in a lab).
  • It is harder to see mistakes and to correct them. It often requires you to restart an entire experiment from scratch ( can not use the find error tool!)
  • I struggled with work hours and location. When I was doing desktop work, I preferred to change my settings and venues. Also I could work whenever I wanted to. You will now be confined to the same building in the same space, everyday. Your progress will also be limited by this.
  • not knowing how much time is 'enough' time spent in doing experiments
  • practical experience is very different from theory - I struggled with dimensions, spatial awareness and quantities. When stuck behind a laptop all day, you lose touch of how much space (and mass) 1 litre of water would take up compared to 1 litre of ice.
  • when reporting back, colleagues are less interested in your journey to the result or your assumptions. They want results and graphs with error bars.
  • you have to be more considerate of your work colleagues space and time as you will sharing equipment. I was so used to be only worried about my computer and laptop
  • your progress seems to be measured on how many times people see you walking up and down to your Lab space ..

Advantages of having done desktop research before:

  • you can use predictive models to predetermine expected behaviour. I do less experiments on average than most of my colleagues
  • we have a slightly stronger grasp of factorial design of experiments (looking at all relevant angles and factors)
  • It seems to come naturally to desktop researchers to immediately interpret results with statistical tools (I am sure you have used a lot)
  • I seem to have some of my final report already typed out - doesn't seem common practice for my colleagues who spend day in and out in the labs.
  • our report writing skills seem to be better - maybe due to sitting in front of the computer all day

  • you are already familiar with the scientific method and hypothesis driven research so this part of the transition is easy.

From laptop work to the social science field ( interviews)


  • you will have to develop real empathy and defer judgement
  • listening is a skill, evenmore so listening and taking notes
  • being objective
  • interpreting results without inferring your own judgement. How does one deal with words and quotes, rather than hard facts and numbers!
  • Must use words like maybe, could be, I think that, whilst being conscious of context all the time! Which differs heavily from the scientific method that must use x is bigger than y by z% because of factor h.
  • Being okay with not having an answer but a description of a scenario.

Advantages of having done desktop work here

  • being analytical
  • being well researched
  • easily find the critical function or important points to investigate

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