Postdoctoral Research Fellow in Marine biodiversity and Machine Learning (ref 229647)

We offer a  postdoc position at the University of Oslo, Department of Biosciences (IBV), Section for Aquatic Biology and Toxicology, within the research project "Coastal ecosystem dynamics under anthropogenic pressures" funded by The Faculty of Mathematics and Natural Sciences. The position is one of 4 positions to be employed within this highly collaborative and interdisciplinary project.

This position is part of a collaborative marine research and training program with a focus on the Skagerrak, Kattegat and Oslofjord (SKO) region to improve marine sustainability and our understanding of the pelagic ecosystem and food-web dynamics in the coastal zone where land and open sea meet. This program aligns with UN sustainability goals considering that the declining fish stocks in SKO will be under scrutiny, as well as the multiple anthropogenic stressors affecting water quality, human recreation and marine life. The project is interdisciplinary, joining a range of key institutions (University of Oslo, Norwegian University for Life Sciences, Norwegian Institute for Water Research, University of Agder, Institute of Marine Research, Norwegian Meteorological Institute) and is embedded in the ongoing strategic institutional SKO initiative. The SKO program at UiO comprises the Departments of Biosciences, Geology, Mathematics and Informatics, and three more people are being recruited in this project.

For this specific position, we will use extensive marine biodiversity data produced by high-throughput sequencing, such as metabarcoding and metagenomics data with corresponding environmental metadata from thousands of samples. These massive datasets, available through public databases and our own collections, comprise sequence information covering the three domains of life and multiple trophic levels from marine coastal systems. This training data will be used to develop classifiers for environmental health assessment, and models to predict tipping points and alternative trajectories of marine biodiversity responses to multiple stressors, as well as model invasive species distributions. Such model predictions are needed to design conservation efforts to dampen marine biodiversity loss, and thus stabilize marine destruction in coastal marine systems.

For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/229647/postdoctoral-research-fellow-in-marine-biodiversity-and-machine-learning