-
to explore GNSS Reflectometry (GNSS R) as a novel, low cost, low power bistatic remote sensing technique optimized for nanosatellite platforms. GNSS R leverages signals of opportunity from existing
-
data science. You must be curious and driven with excellent interpersonal skills and writing competencies. Experience with programming languages, notably Python or R, is expected. The work will imply
-
, Python and/or R, and ability to manage and structure large datasets is essential. Interest/skills in application of AI methods to clinical data is an advantage. Stipend 2: Genetic Risk Communication and
-
skills, Experience in programming in Python or another language, e.g., in C++, Matlab, R, Familiarity with basic concepts of dynamical systems, Knowledge of wind turbine dynamics is a plus, Curiosity to
-
Experience with firm level econometric analyses or with processing of large firm level datasets will be an advantage, but it is more important that you have experience with software tools such as Stata, SAS, R
-
strong competences in ecology, excellent analytical skills, and proficiency in R (or equivalent). Experience within one or more of the following areas is advantageous: insect ecology, species distribution
-
at least one scientific programming environment such as Python, MATLAB, or R. Familiarity with structural degradation phenomena—including fatigue, corrosion, and biofouling—would also be beneficial
-
programming languages such as Python, R, or similar. Qualification requirements PhD stipends are allocated to individuals who hold a Master's degree in Operations Research, Computer Science, Mathematics