Sort by
Refine Your Search
-
Employer
-
Field
-
may also be relevant for the project, such as scalability, post-Bayesian methods, and in general computational and methodological challenges in integrative unsupervised learning. Method development will
-
. Employment is scheduled to start on August 15th, 2026. The BioM Convergence Environment BioM - Methods for knowledge-based biodiversity monitoring and management under uncertainty - is an interdisciplinary
-
conducted In-depth knowledge of qualitative methods and documented experience with long-term, independent ethnographic field research. Strong analytical skills and ability to communicate clearly Ability
-
outreach. Employment is scheduled to start on August 15th, 2026. The BioM Convergence Environment BioM - Methods for knowledge-based biodiversity monitoring and management under uncertainty - is an
-
contribute to developing new methods to advance project aims. Collect, analyse, visualise and interpret data through literature reviews, ethnographic fieldwork, network analysis and other research methods as
-
feasible progress plan. More about the position The position is available for a period of 3 years. There is a 10 % component of the position which is devoted to teaching and administrative duties / other
-
to start in September 2026. The BioM Convergence Environment BioM - Methods for knowledge-based biodiversity monitoring and management under uncertainty - is an interdisciplinary Convergence Environment
-
The application must include Application letter. Please state your motivation and research interests. A tentative project proposal (5-10 pages). The proposal must include the topic, relevant theory and methods and
-
qualitative research methods is an advantage, since the main ARENA activities will centre on interview-based research. Given the interdisciplinary nature of these projects, quantitative methodological skills
-
repositories Proven experience in machine learning method development Fluency in English Desired qualifications Experience analyzing high-dimensional data, in particular single cell transcriptomics/epigenomic