3 trainers found

Expertise academic: History and Philosophy of S...  or Cancer Genomics  or Ecosystem science 


Aidan Wilson

Aidan Wilson is Intersect's Digital Research Services Manager. Before that he had been a Digital Research Analyst at Intersect Australia since 2015, and in that time has been central to the administration and delivery of Intersect's training platform. Besides delivering training at ACU and...

Location: Sydney, NSW

Wilson Aidan aidan.wilson@intersect.org.au Sydney, NSW Aidan Wilson is Intersect's Digital Research Services Manager. Before that he had been a Digital Research Analyst at Intersect Australia since 2015, and in that time has been central to the administration and delivery of Intersect's training platform. Besides delivering training at ACU and elsewhere on Python, R, REDCap, Qualtrics and other tools, he also manages the systems within Intersect that enable the organisation to train upwards of 6000 researchers per year. ["English"] https://orcid.org/0000-0001-9858-5470
Nick Wong

Based within the Monash Bioinformatics Platform and a certified Carpentries instructor, Nick is also involved with Monash Data Fluency in training and teaching on genomics, bioinformatics and R.

Location: Melbourne, Australia

Wong Nick nick.wong@monash.edu Melbourne, Australia Based within the Monash Bioinformatics Platform and a certified Carpentries instructor, Nick is also involved with Monash Data Fluency in training and teaching on genomics, bioinformatics and R. ["English", "Chinese"] https://orcid.org/0000-0003-4393-7541
Tim Langlois

Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range...

Location: GitHub

Langlois Tim tim.langlois@uwa.edu.au GitHub Stereo imagery is widely used by research institutions and management bodies around the world as a cost-effective and non-destructive method to research and monitor fish and habitats (Whitmarsh, Fairweather and Huveneers, 2017). Stereo-video can provide accurate and precise size and range measurements and can be used to study spatial and temporal patterns in fish assemblages (McLean et al., 2016), habitat composition and complexity (Collins et al., 2017), behaviour (Goetze et al., 2017), responses to anthropogenic pressures (Bosch et al., 2022) and the recovery and growth of benthic fauna (Langlois et al. 2020). It is important that users of stereo-video collect, annotate, quality control and store their data in a consistent manner, to ensure data produced is of the highest quality possible and to enable large scale collaborations. Here we collate existing best practices and propose new tools to equip ecologists to ensure that all aspects of the stereo-video workflow are performed in a consistent way. ["English", "French"] https://orcid.org/0000-0001-6404-4000