Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
structured training and supervision of more than 1,500 doctoral candidates in mathematics, natural and life sciences. Working on research projects towards their doctorate, the students are supported in
-
programming skills. Strong skills in mathematics, excellent capacity for mathematical formalism, and ability to grasp new concepts quickly. Solid training in control of marine vehicles abd/or robots, and
-
. Additional training in machine learning methods is an advantage. Solid programming skills. Strong skills in mathematics, excellent capacity for mathematical formalism, and ability to grasp new concepts quickly
-
strong scientific interests and self-motivation. They will have a degree in physics, mathematics, oceanography, meteorology, or a related science with good computing and numerical skills. Entry
-
Do you like applying mathematical theories in practice to solve real-world challenges? Do you like working with top-notch, internationally recognized industrial partners? Would you like to push the
-
that are compatible with benign conditions for life in different planetary environments? How do we characterise the environments on Earth and other planets that could act as the cradle of prebiotic chemistry and life
-
of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU
-
be in advanced courses in computer science, mathematics, AI, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected
-
been funded by the Bavarian state and the University of Würzburg. The GSLS is composed of five sections specialising in different aspects of the life sciences and offers a three-year doctoral study
-
simulations, complex systems analysis or other data-driven methods. Requirements The candidate based at CWI will have either a computer science or mathematics background, with a strong affinity for energy