Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Weihenstephan-Triesdorf University of Applied Sciences (HSWT). As part of an applied research collaboration, a PhD position is available at the high-tech startup lifespin GmbH in Regensburg. The doctoral degree
-
field such as computer science, bioinformatics, mathematics, computational life sciences, or related. Profound knowledge in machine learning, preferably deep learning for image data. Experience in
-
degree in Computer Science or Mathematics. - an interest in machine learning and game theory. - excellent communication skills in English. If you fit this profile, like challenging tasks, and are
-
, support lab courses, and supervise student research. Your profile: Above-average master’s degree in computer science, electrical or mechanical engineering, applied mathematics, or a similar engineering
-
and satellite-based remote sensing data Presentation of your results on conferences and publications in scientific journals REQUIREMENTS: An above-average degree in mathematics, computer science
-
good publication track record Above-average master’s degree in computer science, electrical/ mechanical engineering, applied mathematics, or a similar engineering-oriented quantitative discipline
-
technology, and process optimization using mathematic modeling - Evaluate modified growth factors under real conditions with medium recycling - Independent work on research projects - Close cooperation with
-
of AI. The ideal candidates will have a background in computer science, statistics, mathematics, or related fields, as well as an interest in social science research methods and theories. The PhD
-
mathematics, computer science, information technology, electrical engineering, physics, mechanical engineering, or a comparable qualification Sound knowledge of mathematics and physics, especially in the fields
-
, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since