[Postdoc job] Germany: Deep learning x computer vision x biodiversity

[Masahiro Ryo]

Subject to funding, we are offering a full-time, 1-year (with the possibility of 3 year extension) postdoctoral researcher position starting from 01.11.2023 at our location in Müncheberg, Germany (near Berlin) as:

Postdoc researcher for deep learning image analysis for biodiversity and ecosystem conservation

Your tasks:

• facilitating interactions among collaborators for know-how transfer (monthly meeting)
• taking a leading role in full proposal writing (deadline: 30.04.2024) – upon success, a 3 year extension will be possible
• writing a review article that summarizes an overview of existing DL methods useful for the project
• applying DL algorithms which do not require any annotated images (e.g. Segment Anything Model, Semantic Clustering by Adopting Nearest Neighbors, and Self-supervised Transformer with Energy-based Graph Optimization) to analyze the LUCAS dataset (https://esdac.jrc.ec.europa.eu/projects/lucas)

Your qualifications:

• academic background in the field of Computer Science, Informatics, Mathematics, Environmental Science, Agriculture or related fields
• strong programming expertise in DL applications with computer vision in Python
• ability to work independently as an established scientist (proven by completed doctorate/PhD or equivalent publication successes)
• willingness to answer: What is the current best practice of DL for analyzing images without having a large number of annotations? How can computer vision be used for biodiversity conservation?
• (ideal but not mandatory) experience in using pytorch and one of the above-mentioned techniques or equivalent
• (ideal but not mandatory) fluent in German
  
  For more details and application, see:
  https://jobs.zalf.de/jobposting/e92747d855ea234ed7d6ede1d68822a4894bd0a20?ref=homepage