Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- Aarhus University
- Aalborg University
- University of Copenhagen
- Aarhus University (AU)
- Aalborg Universitet
- Technical University Of Denmark
- University of Southern Denmark (SDU)
- Geological Survey of Denmark and Greenland (GEUS)
- Technical University of Denmark
- Roskilde University
- Technical University of Denmark (DTU)
- Aarhus University;
- Copenhagen Business School
- RegionH
- University of Southern Denmark
- University of Southern Denmark;
- 6 more »
- « less
-
Field
-
sensor data, and (iii) sophisticated fatigue analysis models combining advanced fracture mechanics with crack initiation and growth simulation. Additionally, you will explore fatigue mitigation strategies
-
classical statistical methods (analysis of variance, regression, mixed model analysis, generalised linear models, categorical data analysis, non-parametric analysis, multivariate statistics). Who we
-
you to have: A PhD degree and a strong record of independent epidemiological research. Substantial experience with population-based register research and the analysis of large-scale longitudinal data
-
Very good knowledge of English (written and oral) Good communication skills (scientific community, the public, stakeholders, and managers) Experience in data analysis and statistical tools Preferable
-
/or eating disorders, data analysis and statistical modeling. Prior experience working with Danish registers is an advantage. As a person, the ideal candidate will have good interpersonal skills, will
-
are expected to have experience with data analysis in a clinical context, as well as programming skills in R or Python and familiarity with command-line tools. Experience with data management and the
-
to experimentally derived disorder models and data from methods such as total scattering/pair distribution function analysis, diffuse scattering, diffraction, solid-state NMR and electron microscopy. Work closely
-
differentiation (ideally mouse ESCs), single cell sequencing, method development, flow cytometry/FACS, and/or CRISPR-based perturbations, data analysis. Theoretical background in epigenetics and embryonic
-
numerical modelling, simulation, optimization, control, or engineering-data analysis. Good programming skills in Python, MATLAB/Simulink, or a comparable scientific computing environment. A fundamental
-
. The project will provide training in paleoceanography and paleoclimate research, including the development and interpretation of proxy records, quantitative analysis of environmental data and integration