- Institutions
- Government agencies
- NGOs
- Other researchers
- Physicians
- Students
Inclduing:
- Preparation of research questions
- Study design development and implementation
- Systematic literature review
- Statistics and data analysis
- Scientific writing
- Graphical presentation of results
- Creation and deplyment of interactive dashboards of diverse scientific data
Expertise offered
Bridging academia, business, industry and NGOs
→ Interdisciplinarity
From field & lab work to data science & publishing
→ Full scientific project cycle
Work with multidisciplinary teams
→ Communication across different research areas
Sampling in rivers, lakes, caves, forests and grasslands.
Measure pH, O2, conductivity & other characteristics of ecosystems.
Collecting environmental and bio-samples.
Data Analysis & Visualisation & Data Journalism
After the data is collected, several data science methods are required. SQL and R are used for data extraction and processing. R, RPubs and Phyton will be used for data analysis and graphical presentation of results.
Reports & peer-reviewed scientific publications
Finally, the story needs to be told.
Starting with the background of the research area, leading to the questions and hypotheses, it is necessary to describe the methods, present the results, and discuss them.
Collaborations
- Department of Biology, University of Neuchâtel
- Faculty of Biology and Medicine, University of Lausanne (UNIL)