Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus University Denmark

This postdoctoral researcher position at Aarhus University Denmark focuses on ecological knowledge-guided machine learning, indicating a role that combines expertise in ecology with advanced machine learning techniques. The ideal candidate is expected to have a strong background in ecological sciences, including understanding ecological systems, processes, and data. Additionally, proficiency in machine learning methods is essential, particularly in applying domain knowledge to guide algorithm development and improve model interpretability and performance within ecological contexts. Skills likely include programming languages commonly used in machine learning such as Python or R, familiarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn), and experience with data analysis and statistical modeling. The role may also require experience handling ecological datasets, integrating heterogeneous data sources, and applying knowledge-driven constraints or priors to machine learning models. Strong analytical skills, problem-solving abilities, and the capacity to work in interdisciplinary teams are important. Given the academic nature of the position, a PhD in ecology, environmental science, computer science, or a related field with a focus on machine learning applications is implied. The candidate should demonstrate research experience in ecological modeling, machine learning, or data science, supported by publications or projects. Effective communication skills for scientific dissemination and collaboration within research groups are also essential. Overall, this position demands a blend of ecological expertise and advanced computational skills to innovate in ecological data analysis through knowledge-guided machine learning approaches.