Wissen kann man sich anlesen, Erfahrung nicht. Da sich die meisten Akademiker gerne einlesen, sind die Antworten im Vorstellungsgespräch sehr ähnlich. Das hat zwei mögliche Konsequenzen: Der Personaler ist gelangweilt oder er fühlt sich durch die 08/15-Antworten provoziert. Beide Reaktionen haben meist ein gemeinsames Ende: Die Stelle bekommt jemand anderes.

Das Seminar zeigt auf, wie Sie sich ideal auf ein solches Gespräch vorbereiten, 08/15-Antworten vermeiden und wie Sie den Personaler mit Ihrer Persönlichkeit von sich und Ihren Gehaltsvorstellungen überzeugen.

• Die Teilnehmer/innen lernen mentale Lösungsstrategien in Stressinterviews.
• Durch Übungen wird die Schlagfertigkeit im Gespräch deutlich erhöht.
• Die Teilnehmer/innen lernen in Drucksituationen gelassen zu bleiben und angemessen zu reagieren.
• Jede/r Teilnehmer/in durchläuft ein Stressinterview, um seine erarbeiteten Strategien 
  „live“ zu testen und anschließend zu verbessern. 

A cooperation of InGrA and PhD network.

Any responsible conduct of research should be based on honesty, accuracy, efficiency, and objectivity. The one-day workshop Good Scientific Practice focuses on these scientific standards of international research. It raises awareness of the subject matter by providing doctoral candidates with a set of professional values and ethical norms as well as required competencies and skills to pursue scientific integrity. The content of the course follows the curriculum “Safeguarding Good Scientific Practice” (Memorandum and Code of Conduct) of the Deutsche Forschungsgemeinschaft (DFG).

• Introduction to good scientific practice
• Mentoring in the science system
• Misconduct in scientific research
• Conflicts of interest in scientific cooperation
• Data management
• Publication ethics

The workshop instructs participants on the principles of good scientific practice. Doctoral candidates learn how to comply with the international values and standards of good scientific research and ethical practice.

For many young scientists writing is the most difficult part of research work. Poor structure, breakneck formulations and unclear argumentation lead to texts which are not too user friendly. However, for the success of academics it is essential that the content is successfully conveyed to the relevant target groups – from the subject community to the wider public.

The methods and instruments of scientific writing can be learnt. With a few select mechanisms for structuring and techniques for building arguments, it becomes possible to articulate even complex data clearly and comprehensibly. Coherently built up and convincingly formulated, even academic texts can be an exciting read!

Doctoral students working in natural and life sciences

R has become a leading statistical programming language in data science and statistics. The R software is free, highly extensible, and allows to easily produce publication-quality plots. The aim of this course is to equip participants with the basic skills to effectively use the software R, embedded in the user interface RStudio. These skills will cover data import, processing and data exploration, graphical representations with ggplot2, basic concepts of statistical inference and linear regression. All topics will be demonstrated in working examples and practiced with hands on examples.

The course will be split in two parts. In the first two days we are going to teach the basic functionality of R, RStudio, and ggplot2. Day three and four are dedicated to the application of statistical tests, which will be extended to linear mixed-effects models.

Doctoral students and Postdocs which want to become acquainted with the R language and the basics of linear regression and model selection. No previous knowledge in R or statistics will be required.