Sort by
Refine Your Search
-
Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Position - Denoising Methods for Dual-Tracer PET Imaging Positron emission tomography (PET) is often used to diagnose
-
environmental geophysics. This PhD project aims to advance the process-based understanding of SSF by combining state-of-the-art geophysical methods with controlled field experiments and numerical modeling
-
a related discipline Experience with surface X-ray scattering methods Experience using synchrotron radiation facilities Experience in catalysis and recycling Knowledge of interfaces science Knowledge
-
further develop standardised methods for examining irradiated samples after irradiation to quantify radiation damage. Supervision of the manufacture and assembly of equipment inside and outside hot cells
-
Your Job: The PhD position is offered within the Cluster of Excellence PhenoRob – Robotics and Phenotyping for Sustainable Crop Production. We are looking for a highly motivated PhD candidate
-
» Biology Physics » Biophysics Chemistry » Biochemistry Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 4 May 2026 - 23:59 (Europe/Berlin) Country Germany Type
-
various branch offices) is available at https://www.fz-juelich.de/en/careers/phd In addition to exciting tasks and a collegial working environment, we offer you much more: https://go.fzj.de/benefits We
-
. This highly interdisciplinary PhD project involves synthesising ring polymers and studying them systematically using a combination of neutron scattering and nuclear magnetic resonance (NMR) methods. During
-
Your Job: This position focuses on building, operating, and testing superconducting quantum devices. Your tasks in detail are: Design and fabrication of superconducting quantum circuits Setting up experimental systems for cryogenic measurements Development of a microwave quantum control &...
-
of data scientists, software engineers, and experimental researchers on topics including: Developing multi-scale and multi-modal representation learning methods for scientific imaging data (e.g., SEM