CDT training programme
Materials from the tutorials and other training activities organised by the CDT.
Career Development
Have you ever been asked: What do you want to do in your PhD? What do you want to do after graduation? We often assume that we should just know the answers. But coming up with them is actually really hard---not least because there are no correct answers but only guesses. And they will even change over time!
We have thus put together a series of training sessions on realistic and purposeful planning. The programme is partly hands-on; we will guide you to develop a flexible plan that spans your PhD and the first year(s) after.
The programme consists of the following four sessions:
- Friday 13 October -- Identifying and formulating a long term vision
- Friday 20 October -- Turning the vision into an actionable plan
- Friday 3 November -- Dealing with roadblocks
- Friday 17 November -- Connecting and working with people
The sessions run from 10.30am to 12 (in room G.03 in the Bayes Centre). At the end of the programme, we will further have a "graduation" reception (date and format will be announced later).
You can find further information here: https://michaelgutmann.github.io/goodplanning/
The programme brings together students from different doctoral training programmes in Edinburgh; you will thus likely meet new interesting people!
Session 1 on 13 October: Understand yourself - Developing a Career Vision workbook and Biomedical AI CDT - Understand Yourself slides
Session 2 on 20 October: Turning the vision into an actionable plan
Session 3 on 3 November: Dealing with Roadblocks and Difficulties
Publishing your research in the age of Open Science
One of the principles underpinning and enabling Open Science is Open Access - where authors make their research publications freely available on the internet, distributed under an open license and not locked behind subscription paywalls. Come along to this session to find out what you need to do when you publish your next research article, learn what the research councils expect from researchers and what direct support is available to you to publish Open Access (OA):
- depositing a copy of your paper in an open access repository (Green open access)
- paying an Article Processing Charge (APC) to a publisher (paid Gold open access)
- finding a free Gold open access journal to publish in.
Presenter: Dr Theo Andrew, Scholarly Communications Manager, Library & University Collections
Git: The basics and beyond
Two part series providing an intro to Git, designed for the Biomedical AI PhD CDT cohort, University of Edinburgh (Jan-Feb 2023).
Anna is a third year PhD student in the School of Informatics, interested in the neural circuits underlying honeybee communication. She has held several positions in industry prior to her PhD, including at Microsoft Research Ltd and the research engineering team at The Alan Turing Institute. Although she has designed these tutorials for the context of a PhD, she also hopes to share tips and concepts that are applicable to a wide range of contexts based on her experience of Git over the past five years.
Two part series providing an intro to Git, designed for the Biomedical AI PhD CDT cohort, University of Edinburgh (Jan-Feb 2023).
Part 1
The first lecture covers the following topics:
- Version control workflow
- Branching
- Merging
- Remotes
https://media.ed.ac.uk/media/Git%2C+The+basics+and+beyond+Part+1/1_4mj29khb
Part 2
The second lecture covers the following topics:
- Open source contributions
- Handling big repositories
- Debugging
- Git hooks
https://media.ed.ac.uk/media/Git%2C+The+basics+and+beyond+part+2/1_x105594j
Preparing for Job Interviews
A discussion of the interviewer's perspective on recruitment, including advice on being noticed and passing the interviews. The material focusses on Machine Learning interviews.
Plotting in Python
This tutorial is a simple researcher's guide to plotting in python. It covers the basic object-oriented mechanics of matplotlib and how to build your own set of useful plotting functions suitable for research.
Along the way, we will discuss specific tips and tricks like: why formatting many subplots is surprisingly hard (and how to fix it), how to globally configure matplotlib settings like font sizes, automatic saving of data to enable rapid editing of figures, manual editing of vector graphics and more.
https://git.ecdf.ed.ac.uk/bmai-cdt/training/plotting-in-python
Creating Scientific Figures in Inkscape
This workshop covers the basics of Inkscape as well as several of its more advanced features that are useful for making scientific figures. Topics covered: - Shape and text manipulation and arrangement - Image cropping and vectorization - Using LaTeX in Inkscape Link to workshop materials: https://git.ecdf.ed.ac.uk/bmai-cdt/training/inkscape
- Video: Creating Scientific Figures in Inkscape
- This workshop covers the basics of Inkscape as well as several of its more advanced features that are useful for making scientific figures. Topics covered: - Shape and text manipulation and arrangement - Image cropping and vectorization - Using LaTeX in Inkscape Link to workshop materials: https://git.ecdf.ed.ac.uk/bmai-cdt/training/inkscape About the author: Dominic Phillips is an PhD researcher in Biomedical AI at the University of Edinburgh. You can read more about his work here: https://web.inf.ed.ac.uk/cdt/biomedical-ai/people/doctoral-researchers/2021-cohort
Research Data Management
Research Data Management (RDM) is the methodical handling of the information produced or re-used during the course of academic research. It is a policy requirement of many funders and a legal responsibility. The outcomes of good RDM are that the rights of data subjects/owners are protected and that data is archived towards the end of research so that it remains available for validation of results, and potentially for future re-use.
Writing a Data Management Ppan will help you improve your data management practices and ascertain how to organise and publish your code & data so that it is maximally accessible. It is useful for others as it allows them to more easily reproduce and build on your research. It is also useful to you, or future you, as it makes it easier to get back into things e.g. after a longer paper review period, or just a break.
The University’s Research Data Service can provide support on preparing a DMP, as well as a variety of other services, tools and training to help you effectively manage and share data produced or re-used in your research project.
Training sessions on research data management and DMP are held in the CDT every year. Slides for the 2023 session can be accessed here:
Data Management Plan 2022