Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
engineering, computational biology, biostatistics, or a related discipline, with a strong background in clinical data analysis and predictive modeling. Experience with multivariate regression techniques
-
Facility (ViSp) is a central infrastructure for this project (https://www.umu.se/en/research/infrastructure/visp/ ). The scholarship (30 000 sek/month) is funded by the Carl Trygger Foundation and the
-
multivariate analyses, particularly regression analyses (linear, logistic, multinomial, Poisson). Experience with data management, production of ongoing data reporting and graphics/table creation Experience
-
. Extensive knowledge of statistical methods including multivariate and univariate analysis of large data sets, learning and predictive modeling, network analysis, and probabilistic approaches to test theories
-
Number AE2026-0029 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2026-0029.pdf CALL FOR GRANT
-
, or scientific publications Experience in statistical analysis of data including univariate, multivariate statistics Science communication skills proven publication record in international peer-reviewed journals
-
Statistics (Ref: FST241106) Job Description Candidates with expertise in one or more of the following areas: Linear Algebra, Calculus, Statistics and Probability, Regression Analysis, Multivariate Analysis
-
within the PhD trajectory? You can read more about this on this page . Your work includes: development and application of image-processing pipelines; multivariate modelling using network analysis and
-
size and density approaches. Demonstrated experience in infrared spectroscopy of soils and use of multivariate statistical models to predict soil properties. Experience in process-based models
-
statistical multivariate methods to extract spatio-temporal spike patterns. Finally both results will be linked and related in space and time and to behavioral events. Core Tasks: Getting familiar with