Training organised by Postdoctoral Hub

Venue: Krystal, Ústřední knihovna

Lecturer: Mgr. Lucie Hošková, Central Library

Educational Portal: more information and registration here

R is an open source programming language widely used in the scientific sphere for its robust data analysis and especially its data visualization. On this half-day course we will go through the data visualization tools in base R, but spend most of our focus on the powerful and simple-to-use ggplot2 data visualization package.

To take part of the course, a basic understanding of R is expected (loading data, naming and using variables, orientation in basic data types).

Learning outcomes: At the end of the course the participants will be able to use R for creating customizable data vizualizations of their research data.

Topics that will be covered:

• visualization in base R

• when do I choose which graph type?

• bar plot, line chart, histogram

• ggplot2 package

• aes function

• colors

• scatterplot, box plot, heat map, spatial data visualization

Venue: Kampus Hybernská

Lecturer: Mgr. Ondřej Daniel, Ph.D., Research Support Office

Educational Portal: more information and registration here

This workshop introduces key principles of research ethics and their practical application throughout the research lifecycle. Participants will explore how ethical considerations shape responsible research practice and how they should be addressed in research project proposals. The workshop will also provide practical guidance on preparing an Ethics Management Plan, including how to identify potential ethical issues and design appropriate mitigation measures. Through examples and discussion, postdoctoral researchers will gain a clearer understanding of ethical responsibilities in research, strengthen their ability to address ethics requirements in grant proposals, and learn how to plan and manage ethical aspects during project implementation. The workshop is open to postdoctoral researchers interested in strengthening their competencies in responsible and ethically sound research.

Venue: online

Lecturer: Mgr. Dagmar Hanzlíková, Ing. Milan Janíček – Open Science Support Centre

Educational Portal: more information and registration here

This course will introduce the basic principles of open science practices and will further focus on open access publishing and opening the publication process. The attendees will learn about different strategies how to provide open access to their publications and how to make their work reusable. The module will also cover the basics of copyright and licensing with a particular focus on Creative Commons licenses. Finally, the course will introduce other ways of opening the publication process such as preprints, preregistrations or open peer review.

Venue: online

Lecturer: Mgr. Dagmar Hanzlíková, Ing. Milan Janíček – Open Science Support Centre

Educational Portal: more information and registration here

The attendees will learn how to manage their research data in accordance with the FAIR principles and how to develop a data management plan. The course will further introduce how to make research outputs reusable and how to responsibly share research data in line with the principle “as open as possible, as closed as necessary.

Venue: Krystal, Ústřední knihovna

Lecturer: Mgr. Lucie Hošková, Central Library

Educational Portal: more information and registration here

R is an open source programming language widely used in the scientific sphere for its robust data analysis and especially its data visualization. On this half-day course we will go through the data visualization tools in base R, but spend most of our focus on the powerful and simple-to-use ggplot2 data visualization package.

To take part of the course, a basic understanding of R is expected (loading data, naming and using variables, orientation in basic data types).

Learning outcomes: At the end of the course the participants will be able to use R for creating customizable data vizualizations of their research data.

Topics that will be covered:

• visualization in base R

• when do I choose which graph type?

• bar plot, line chart, histogram

• ggplot2 package

• aes function

• colors

• scatterplot, box plot, heat map, spatial data visualization

Venue: Kampus Hybernská

Lecturer: Czexpats in Science

Educational Portal: more information and registration here

This course will cover critical aspects of establishing and managing your own research group, focusing mainly on attracting and hiring the right people and setting rules and procedures in the team. The program combines theory, hands-on exercises and a moderated discussion with a junior Principal investigator, who has successfully tackled these challenges in her recent transition from the postdoc phase.

Venue: online

Lecturer: Blanka Collis, PhD, Radka Šustrová, PhD - Czexpats in Science

Educational Portal: more information and registration here

The workshop will focus on transforming ideas for a research project into convincing, ambitious yet feasible grant proposals. Working with their own real-life research projects, participants will engage in practical exercises in small breakout groups and get feedback and insight from successful grant applicants, along with experts from grant offices and funding agencies, equipping them with the skills needed to craft compelling grant proposals across various settings and formats.

Venue: Kampus Hybernská

Lecturer: prof. Dr. Julia Mildorfova Leventon

Educational Portal: more information and registration here

Many research programmes and activities call for interdisciplinary research for solving complex problems. This interdisciplinary research can take many forms depending on how methods and disciplines are combined, for what purpose, and how that mixing occurs. Different types of interdisciplinarity pose challenges to researchers, around how they cross paradigms and different understandings of core concepts, and navigate research team dynamics. In this workshop, we start with the building blocks of research design (e.g. concepts, data collection methods, data analysis methods, case studies, etc.) and explore approaches to put together these building blocks in different research designs. We consider how approaches match research aims, and create challenges and opportunities for knowledge integration. We also learn from practice, and reflect on the risks and difficulties of doing interdisciplinarity, including those relating to collaboration and team management.Programme description:

By the end of this workshop, postdocs will be able to

• Recognise and identify core building blocks of interdisciplinary and transdisciplinary research.

• Design interdisciplinary research that mixes methods and disciplines, from simple to complex projects.

• Identify and manage common challenges in interdisciplinary research in practice.

Workshop approach

This workshop includes a range of teaching approaches, and relies on the participants being engaged and participating in discussions. Lecturing is used only to create core understandings of key definitions being used. We will spend more time creating research designs (we will even physically build them with Lego), sharing ideas, and participating in structured discussions and participatory exercises. 

Suggested advance reading

Chapter 1: The Selection of a Research Approach in Creswell, J.W., 2014, Research Design: Qualitative, quantitative and mixed methods approaches.

Freeth, R., & Caniglia, G. (2020). Learning to collaborate while collaborating: advancing interdisciplinary sustainability research. Sustainability science, 15(1), 247-261.