Sort by
Refine Your Search
-
genomic summary statistics (e.g., diversity, inbreeding, mutational load) Interest in machine learning applications (experience is a plus but not required) A strong understanding of evolutionary and
-
engineering, with a strong willingness to learn the complementary skill set. Experience in collaborative research environments. Excellent communication and teamwork skills. A proactive attitude towards learning
-
(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
-
supervision experience at the BSc and MSc level Interest and experience in developing competitive national and international research applications Experience in programming languages (e.g. Python/R) and
-
or laboratory analyses. Familiarity with statistical analyses and data integration across multiple sources. Collaborative skills and ability to demonstrate commitment in teams Motivation to pursue a scientific
-
of metabarcoding data, plant metabolomics or transcriptomics, multivariate statistical analyses or soil microbiology Further, we will prefer candidates with some of the following qualifications: Teaching and
-
approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers
-
Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
and scenario models Experience and understanding in statistical analyses. Collaborative skills and ability to participate actively in multidisciplinary teams A fondness for taking the initiative and the
-
, or landscape modelling Further, we will prefer candidates with some of the following qualifications: Teaching and supervision experience at the BSc and MSc level Interest and preferably experience in developing