Transferable Skills
Transferable Skills – Schlüsselqualifikationen für die universitäre und ausseruniversitäre Laufbahn
- individuelles Feedback von Expertinnen und Experten
- intensives Lernen in kleinen Gruppen
- fächerübergreifende Vernetzung
Transferable Skills sind Kompetenzen, die man in einem Kontext erwirbt und dann in verschiedenen Kontexten, Jobs, Positionen, Funktionen oder Aufgabenbereichen einsetzen kann. Beispielsweise braucht man sowohl im Forschungskontext als auch in anderen Bereichen (Bauvorhaben, Entwicklungsprojekt, Werbe- oder Wahlkampagne) ein gutes Projektmanagement.
By topic
Courses that deal partially or entirely with AI are marked with an asterisk (*).
Interpersonal & Management
- How to achieve high performance as a scientist
- Leadership Toolbox
- Project management for efficient research
- Career outside academia (April)
- Publishing Strategies for PhD candidates
- Prompt Engineering and AI Toolkit for Researchers*
- Profiling Journals for Scientific Publication
- Engaging in Policymaking as a Researcher
- Career outside academia (June)
- Build your own personal AI-Assistants*
Writing
- How to write a competitive research grant proposal and fellowship application (February, March)*
- Designing manuscripts with LaTeX*
- From Search to Submission: Using AI Tools and Agents Across the Research Workflow*
- How to write a SNSF narrative CV with AI assistance*
- Peer Reviewing Effectively and Efficiently
- How to write a competitive research grant proposal and fellowship application (April, May)*
- Using AI responsibly for searching, reading, and writing: Critical thinking and sustainable best practices*
Data Management
- Getting Started with 'R' – Analysing and Visualising your Statistical Data (March)
- Building Better Research Software
- Introduction to Research Data Management
- AI-Powered Methods and Tools for Research
- Introduction to data science with Python and AI coding assistants
- Introduction to Image Processing with Python
- Getting Started with 'R' – Analysing and Visualising your Statistical Data (June)
Scientific & Research Integrity
By date
| Title | Dates |
|---|---|
| February 10, 2026 8:30 a.m.-12 p.m. | |
Best practices for storytelling with your scientific presentation |
February 11-13, 2026 9 a.m.-5 p.m. |
| February 16 & 23, 2026 9 a.m.-12:30 p.m. | |
| February 18, 2026 9 a.m.-5 p.m. | |
How to write a competitive research grant proposal and fellowship application |
February 25, March 04 & 11, 2026 8:30 a.m.-12 p.m. |
| February 26, 2026 12:15 p.m.-2 p.m. | |
| February 27 & March 13, 2026 10 a.m.-4 p.m. | |
From Search to Submission: Using AI Tools and Agents Across the Research Workflow |
March 2, 9 & 16, 2026 8:30 a.m.-2 p.m. |
| March 18, 2026 8:30 a.m.-12 p.m. | |
| March 20 & 27, April 10 & 17, 2026 8 a.m.-12 a.m. | |
| March 23 & 30, 2026 8:30 a.m.-5 p.m. | |
Getting started with 'R' – analysing and visualising your statistical data |
March 25-27, 2026 8 a.m.-4 p.m. |
| March 31, 2026; 2 p.m.-5:30 p.m. | |
| April 20 & 27, May 04, 2026 8:30 a.m.-12 p.m. | |
| April 21, 2026 10:15 a.m.-12 p.m. | |
How to write a competitive research grant proposal and fellowship application |
April 22 & 29, May 06, 2026 8:30 a.m.-12 p.m. |
| April 24 & May 01, 2026 10 a.m.-6 p.m. | |
| April 27 & May 18, 2026 12:15 p.m.-4 p.m. | |
| April 28 & May 05, 2026 9:15 a.m.-5 p.m. | |
| May 19, 2026 2 p.m.-5:30 p.m. | |
| May 20, 2026; 9 a.m.-5 p.m. | |
| May 21, 2026 1 p.m.-5 p.m. | |
Introduction to data science with Python and AI coding assistants |
May 26-28, 2026 9 a.m.-5 p.m. |
| June 08, 2026 8:30 a.m.-5 p.m. | |
Getting started with 'R' – analysing and visualising your statistical data |
June, 10-12, 2026 8 a.m.-4 p.m. |
| June 11 & 18, 2026 10 a.m.-6 p.m. | |
| June 15 & 16, 2026 09 a.m.-5 p.m. | |
| June 22, 2026 9:15 a.m.- 5 p.m. |