PhD student in theoretical ecology
Core
Investigate the relationship between the structural organization of ecological networks and response diversity using network analysis and AI/ML on acoustic data.
Role type
Research-focused PhD candidate (theoretical ecology & bioacoustics)
Builds
Ecological interaction networks and AI pipelines for acoustic data processing
Domain
Ecology, Bioacoustics, Machine Learning, Network Science
Deliverable
Research
Required skills
Network analysis, AI/ML, Ecological modeling, Scientific programming (R/Python/C++), Data analysis
Preferred skills
Bioacoustics, Signal processing, Large dataset analysis
Technologies
R, Python, C++, Acoustic recording tools
Responsibilities
Develop network-analytic methods, Apply AI/ML to identify species interactions, Construct ecological networks, Publish scientific papers, Participate in international network training and secondments
Seniority
PhD Candidate (early career researcher)
