Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
letter) Curriculum vitae Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale A research statement (2-3 pages) explaining your ideas and relevant literature
-
and BSc/MSc diploma (in English) including official description of grading scale A short PhD project proposal (maximum 2 pages plus references) describing a possible research objective, theoretical
-
90 are PhD students, and about 40 % of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model
-
DTU Tenure Track Researcher in Nutrition, Sustainability and Health Promotion with a focus on Sus...
xperience with quantitative research methods, Experience in reproducible statistical analyses (preferably R and Python) and in the peer-reviewed publication of results. Must be able to work interdisciplinary
-
14 Mar 2025 Job Information Organisation/Company Technical University Of Denmark Department DTU management Research Field Mathematics » Statistics Engineering » Other Researcher Profile First Stage
-
teaching courses and co-supervision of BSc and MSc. Qualifications MSc graduates with a background in either engineering, mathematics, computer science, computer engineering, physics, sustainable energy
-
. This entails new models for integrating choice and process data, new statistical inference procedures tailored to such models, and new methods for collecting rich behavioural data in immersive experiments
-
quantitative metrics of faults and defects, integrating statistical metrics into active inspection behaviors. Collaborate with a multidisciplinary team—from the AUTOASSESS project—to integrate your algorithms
-
from many different sources into data frames that can be analyzed with biostatistical applications in the statistical software R/Python. Performing data analysis in accordance with time-structures and
-
is to create and combine knowledge on relevant atmospheric flow statistics with AWE time-domain analysis and uncertainty quantification, to determine loads statistics and failure probabilities