Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
testing, to achieve sub-second cycle times for robotic systems. 3. Demonstrated analytical problem-solving through experimental design, critical quantitative and qualitative data analysis, and validation
-
or computational neuroscience, artificial intelligence, psychology or a related field. strong programming skills. experience in experiments with human participants is preferred. good analytical skills and a positive
-
public audiences and taking part in a pilot programme where experience can be acquired in high school science teaching; use graph theoretical tools to develop new fundamental frameworks and analytic tools
-
motivation to gain experience in) quantitative methods and statistical analysis; excellent analytical proficiency and conceptual understanding; strong communication, presentation, collaboration, networking and
-
comfortable applying analytical thinking to explore research questions and have programming experience (preferably in Python). You have an affinity with coastal numerical modelling, e.g. AeoLiS, XBeach
-
chemical reaction networks with robotic systems and analytical science. You will also learn how to programme robotic systems and how to implement aspects of deep learning and neural networks for reservoir
-
analytical and research skills, with experience in (dynamic) Material Flow Analysis or modelling (required). Knowledge of energy and material systems, and circular economy is an advantage. Excellent written
-
. The candidate will join a lively and highly international team of PhD and Master students working on human demography, and ecology and evolution in wild animals, supported by laboratory and analytical technicians
-
, Quantitative Reasoning and Analytical Writing). Successful applicants typically perform among the top-10% of test-takers on the quantitative part of the GRE; applicants with a Q score below 160 will not be
-
? We are looking for a pro-active, analytical and self-motivated PhD candidate to contribute to our understanding of fire impacts on vegetation and carbon emissions in a rapidly warming Arctic. You will