44 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" PhD scholarships at Leibniz in Germany
Sort by
Refine Your Search
-
/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
-
The Leibniz Institute for Prevention Research and Epidemiology – BIPS in Bremen, Germany, invites applications for its three-year PhD program starting October 1, 2026. BIPS, a leading center for
-
. or comparable) in (bio-)physics, (bio-)chemistry, materials science, mechanical/(bio)chemical engineering or similar fields. Highly motivated and team-oriented Passion for multidisciplinary research and eagerness
-
. or comparable) in (bio-)physics, (bio-)chemistry, materials science, mechanical/(bio)chemical engineering or similar fields. Highly motivated and team-oriented Passion for multidisciplinary research and eagerness
-
an interdisciplinary consortium studying the “GEvol: Genomic Basis of Evolutionary Innovations (GEvol)” (Priority Programme, SPP 2349 funded by German Science Foundation (DFG)). We are recruiting a highly motivated
-
relevance. This project bridges materials science, bioengineering, and cell biology, contributing to the development of advanced biomaterials for tissue engineering and disease modeling. Your profile Master’s
-
CANCER (F/M/D) Starting on May 1st, 2026 (with flexibility). We have pioneered the development of synthetic tumor immune microenvironments, engineered from artificial cells that mimic immune functions
-
and technologies. The institute employs an average of 500 people from over 40 nations and, in addition to its scientific tasks, is dedicated to promoting young scientists and engineers. The IFW supports
-
and technologies. The institute employs an average of 500 people from over 40 nations and, in addition to its scientific tasks, is dedicated to promoting young scientists and engineers. The IFW supports
-
yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at leveraging graph-theoretic approaches to analyze and predict food-effector