Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Max Planck Institute for Evolutionary Biology, Plön | Plon, Schleswig Holstein | Germany | 29 days ago
the genetic architecture of a polygenic trait, embryo size in Drosophila, and to study the effect of distance to trait optimum on the adaptive architecture. Our group has recently developed an accurate and high
-
the practical adoption of IBFD. In this postdoctoral project, you will investigate novel integrated microwave circuit architectures that address the front-end challenges of IBFD in MIMO systems. The research will
-
does not support Zip files. CV A comprehensive CV, including a complete list of publications. PhD thesis thesis together with the transcripts Personal letter A summary of your previous research fields
-
support Zip files. Degree certificates and grade transcripts (master's, PhD) CV (max 2 pages) A comprehensive CV, including a complete list of publications. Personal letter (max 2 pages) A brief
-
on resilient 6G connectivity for mission-critical applications, and contribute to innovative European and Dutch national projects together with a team of talented PhD researchers? Information The future 6G
-
(cover letter) CV Academic Diplomas (MSc/PhD – in English) List of publications A mandatory research statement (max. 2 pages) describing your understanding and achievements in optical computing for neural
-
, depending on the candidate’s experience and merits. About the project and group The Nanoscale Architecture Lipid Flux – Veijo Salo research group aims to uncover the molecular logic of lipid flux and
-
. Candidates should also have an ability to conduct independent research, take initiative, ask pertinent scientific questions, and interact with other scientists. A PhD in molecular biology, genetics
-
deadline A research profile in 6G/wireless technologies and/or free-space optical communications What you will do Supervise master’s and/or PhD students to a certain extent Possibility to engage in teaching
-
: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design Creating and validating digital twin architectures that incorporate physical laws and constraints