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Workshop Description
This workshop is tailored to equip postdoctoral researchers with a broad understanding of strategies, tools, techniques, and shared experiences crucial for managing research projects at the postdoc level. The content spans key areas such as knowledge management, progress tracking, advanced analysis and software utilization, comprehensive reporting, and dissemination, code preservation and reproducibility as well as interpersonal skills and team dynamics. The technical aspects of the workshop are particularly geared towards projects centered around data and analysis. We will delve into best practices and common pitfalls (the “dos and don'ts”), and the workshop will include ample opportunity for discussion and the sharing of personal experiences among participants.
List of the learning outcomes
Knowledge management:
- Acquiring, organizing, preserving knowledge
- Knowledge and reference management tools
Progress management:
- Quick note-taking, Progress logs, Gantt chart and thinking ahead
- Project management tools
Analysis and software management:
- Inline code documentation
- Function and module-based code development
- Version control – Git and GitHub
- Dependency and environment management – R and Python
- Creating packages – R and Python
- Containers - Docker
Reporting and dissemination:
- Notebook style – Jupyter and Quarto
- Interactive style - Shiny and Streamlit
- Github
- Zenodo
Using AI:
- Planning
- Organizing
- Implementing
- Risks and benefits
Teamwork and coordination:
- Progress update to collaborators
- Self-assessment of the progress
- Future perspective
Prerequisites
PhD
Target audience
The course is ideally designed for early-stage postdoctoral researchers but those beyond the first year can benefit from the course as well.
Duration of the workshop
3 x ? days
Day 1: Monday, 20 April : 13:00-16:00
Day 2: Tuesday, 21 April : 13:00-16:00
Day 3: Wednesday, 22 April : 13:00-16:00
Instructors:
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Fully booked. Sign up for waiting list.