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Are you a UK-based doctoral student who is keen to further develop your skills? The Doctoral Landscape Training Network (DLTN) is a network of UKRI-funded doctoral training programmes that aims to provide advanced training in research skills for students enrolled in doctoral research, particularly students enrolled in UKRI-funded programmes.
On this site you can find details of upcoming courses currently offered by DLTN programmes and partner organisations. If you wish to apply to join a course, please: Ensure that you meet any prerequisites for the course you are applying for. Seek approval to apply to a course from your supervisory team. Ensure that you have access to funding to meet any associated costs.
If you are a UKRI-funded training provider and wish to advertise a course or training opportunity via the DLTN please complete the form available here.
Upcoming Courses:
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Reproducible Reports with Quarto - 22nd July
This on-line workshop introduces you to Quarto, a scientific and technical publishing system designed to facilitate reproducible working practices by allowing you to integrate code, results, and narrative text in a single document. Quarto supports multiple programming languages, including R, Python, Julia, and Observable JavaScript.
The workshop will be taught using R and RStudio, but the concepts are applicable to other programming languages supported by Quarto. Some familiarity with the layout of RStudio and beginner level knowledge of R is assumed.
By the end of this workshop, participants will be able to transform raw data into a professional, polished report (HTML, Word, or PDF) where the text and analysis remain in sync. We will use the Gapminder data on global development to demonstrate how to produce a reproducible country profile report that analyses the relationship between wealth (GDP per capita) and health (Life Expectancy) over the last 50 years.
Registration Link
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Introduction to reproducible data analysis in R - 28-29 July 2026
Location - in person: University of York
This two-day workshop provides a hands-on introduction to reproducible data analysis using R and RStudio, covering essential scientific computing concepts such as file systems, working directories, data organisation, and data visualisation. Through live coding exercises, participants will learn to import, analyse, and present data in R and then apply their skills to biological datasets.
No previous programming experience is required.
The course fee is £150 - lunch is included. We are pleased to offer 10 travel scholarships of up to £200 to help cover travel and accommodation costs.
Registration Link
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AICatalyst2026: AI in the Biosciences Training Conference - 4th September 2026
Location - in person: The Guildhall York
Free event open to all UK based researchers
This free training conference is organised by the UKRI Digital Research Skills Catalyst, with funding support from AIBIO-UK.
The programme brings together a mix of expert talks and hands-on workshops designed to introduce AI methods in bioscience research.
These sessions will equip you with working knowledge of a wide range of techniques under the AI umbrella, from traditional Machine Learning to Large Language Models, applied to a range of biological applications.
Attendees will also have the opportunity to present their own work through a poster session, allowing you to network and be part of the nascent AI in Bioscience community, as well as potentially win the coveted Poster Prize!
While this conference primarily is targeted at PhD and postgraduate researchers in the biological, medical, and environmental sciences, we welcome professionals at all career stages.
Travel scholarships Through the AIBIO-UK Flexifund, we are pleased to offer travel scholarships to help cover your attendance costs. Standard Travel: Up to £100 per person for economy rail or bus travel Long-Distance Travel: Up to £150 per person for those traveling from further afield who require an overnight stay in York (covers economy travel and hotel expenses) You will need to reclaim these expenses by completing an expense form and submitting receipts after participation in the course. Scholarships will be provided on a first come first served basis. We will contact you within a few days of your registration to confirm whether you have been awarded a scholarship. Lunch and Networking tea/coffee will be included.
Registration Link
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A beginners course in High Parameter Flow Cytometry Data Analysis - 4-5 November 2026
Location - in person: Department of Biology, University of York
Pre-requisites: 1) Your own laptop with Python installed (instructions will be provided). 2) An understanding the basic principles of flow cytometry compensation, plotting fcs data and conventional gating data analysis.
This course is designed to train beginners how to undertake high dimensional flow cytometric analysis. This will be a practical based course with the theory and concepts behind dimensionality reduction and clustering in a manner that is relevant and practical to cytometerists.
No programming experience is required, and so this will be a greater way to remove the barriers to undertaking and supporting deeper flow analysis. It will teach how to use python and flow cytometry analysis software FCS Express (De Novo, Dotmatcs) and will go through the practice as well as the pre-processing tasks required for analysis pipelines.
At the end of the course you should have an understanding of the associated mathematical algorithms, which algorithms to choose, what they illustrate about the data set and how to integrate Python scripts into the FCS Express flow cytometry analysis software. Thanks to our collaborator De Novo Software for helping make this course possible.
Registration Link
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