-
to reconstruct statistically meaningful flow fields. Despite their popularity, both approaches still present major challenges such as large amounts of high-resolution data (from direct numerical simulations
-
partners. Strong applicants typically have backgrounds in computer science, statistics or econometrics but should have an intrinsic interest for marketing problems. The PhD will be supervised by Prof. Dr
-
led to the development of a key statistical tool that paired public sightings of suspected unowned cats with confirmatory data to enable robust estimates of unowned cat populations (termed an integrated
-
candidates with a good understanding of bacterial physiology/genetics and antimicrobial resistance, statistics, and an enthusiasm for mycobacterial research. Experience in some aspects of bacterial culture and
-
Sciences. Our methods are usually founded in Computer Science and Statistics while problems to be solved are often defined by Life Scientists. In collaboration between Professor Komorowski’s Bioinformatics
-
; study design; multidisciplinary analyses (e.g. Genetics, Behaviour, Isotopes); statistical analyses; academic writing. The project is supervised by Dr Lysanne Snijders (Behavioural Ecology group) and Dr
-
strong background and solid hands-on experience in experimental analytical methods, data processing, and statistical analysis; a strong interest (or preferentially: experience) in spectroscopy, microscopy
-
experimental research, including knowledge of and demonstrable experience with applying (state-of-the-art) statistical techniques. Experience with data wrangling (e.g., in R or Phyton). Open-minded and motivated