Sort by
Refine Your Search
-
for a doctoral candidate with the following qualifications: Master's degree in meteorology, physics, mathematics, computer science or an equivalent scientific or mathematical discipline Very good
-
mathematics or a closely related field is required. Experience with some of the following topics will strengthen your application: statistical physics; critical phenomena; interacting point and particle
-
with a master’s degree in mathematics. A strong background in the theory and numerics of partial differential equations and a very good background in optimization and/or stochastic analysis is required
-
for an excellent scientist with a University degree in Meteorology or a related subject such as Physics, Mathematics or Geosciences. Prior experience in analyzing large-volume observational data and with programming
-
through various channels. The ifo will actively support you in this. What we expect from your profile a degree with excellent grades, preferably in economics or mathematics, physics or a related field
-
, computer science, applied mathematics, computational biology, bioinformatics, and many other subjects relevant to the project. Excellent communication skills in English, verbally as well as in scientific
-
PhD candidate. We are looking for a person with a background in (bio-) statistics, mathematics or related disciplines who is interested in longitudinal data analysis, causal inference and applications
-
approaches. Publish results in high-impact journals. Your qualifications and skills: You hold a Master's degree (or equivalent) in mathematics, statistics, biostatistics, bioinformatics, plant breeding
-
The Leibniz Institute for Solid State and Materials Research Dresden e. V. (IFW Dresden) conducts modern materials research on a scientific basis for the development of new and sustainable materials and technologies. The institute employs an average of 500 people from over 40 nations and, in...
-
agronomy, agricultural engineering, geography, mathematics, physics or similar good knowledge of process-based crop modelling (e.g. DSSAT, APSIM, WOFOST, …) computer programming or scripting skills in (e.g