M.Sc. Bernhard Kühn
Institute of Sea FisheriesHerwigstraße 31
- +49 471 94460 254
- +49 471 94460 199
- Population dynamics
- Statistical modelling of fish stocks
- Machine learning in fisheries science
- Pre-processing and modelling of spatio-temporal environmental data sets of the North Atlantic and North Sea.
- Statistical modelling of stock-recruitment dynamics for commercially important fish stocks in the North Sea using environmental parameters.
- Bio-economic modelling with FLBEIA.
Educational background and employment
- Since October 2018 Researcher at the Thuenen Institute for Sea Fisheries in the EU-Project PANDORA.
- 2014 - 2018 Master of science in Environmental Modelling at the Carl-von-Ossietzky University, Oldenburg.
- 2010 – 2014 Bachelor of science in Environmental sciences at the University of Koblenz-Landau, Landau.
Working Groups and Committees
|Working Group - Committee||Tasks|
|Working group on machine learning in marine science (WGMLEARN)||The working group on machine learning in marine science (WGMLEARN) is involved in identifying the current status and potential ways of incorporating machine learning methods in the marine sciences. The goal is to summarize relevant information, identify challenges and needs (methodology and data) and promote the adoption of relevant ML-techniques in the marine science domain.|
- Schäfer R.B, Kühn B., Hauer L., Kattwinkel M., (2017): Assessing recovery of stream insects ¨ from pesticides using a two-patch metapopulation model. Science of The Total Environment, 609: 788-798.
- Schäfer, R. B., Kühn, B., Malaj, E., König, A., & Gergs, R. (2016): Contribution of organic toxicants to multiple stress in river ecosystems. Freshwater biology, 61(12), 2116-2128.
Scroll to top