-
, deep learning Computational genomics, network modeling, spatiotemporal/functional data analysis, time-series Strong programming in R and/or Python; best practices in reproducible research Excellent
-
applicants who combine strong quantitative skills with a deep interest in the fundamental mechanisms shaping plant communities and their response to climate change. Qualifications: • PhD in Ecology or a
-
etc; Candidates with multidisciplinary backgrounds are welcome. · Strong skills in computational and data analytical methodology development and implementation; experience in machine learning and deep
-
healthcare. Qualifications Required: PhD (or equivalent) in computer science, statistics, biostatistics, electrical/biomedical engineering, or related quantitative field. Strong background in machine learning