Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
+ imaging, data analysis and neuronal circuits. Requirement PhD in neuroscience, computer science or a related field High motivation for explorative research Experience in neurophysiology (electrophysiology
-
environment in the fields of science, technology and administration as well as for the education of highly qualified young scientists. The computational imaging group at DESY is concerned with the development
-
activities in circuits of murine models of 22q11.2 and 3q29 deletion syndromes, two rare conditions that confer the highest genetic risks of schizophrenia. Qualifications: PhD in computational neuroscience
-
of personalized solutions we offer. Welcome to the UKE. PhD position / Postdoc position (all genders) in AI for biomedical data analysis Part time | Temporary | Hamburg Eppendorf UKE_Zentrum für Molekulare
-
biological systems, also in collaboration with other researchers and companies. Your profile Applicants should hold a PhD in Computer Science, Computer Engineering, Artificial Intelligence, Physics
-
currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
-
, probabilistic models Representation learning, self-supervised learning, foundation models Data analysis, non-linear statistics, knowledge management Your profile PhD in Computer Science, Bioinformatics
-
, genotyping, immunohistochemistry, RNA in situ hybridization and statistical analyses. Qualifications The ideal candidate should have a PhD in molecular or developmental biology, neurosciences, photoreceptor
-
), including research project supervision and teaching of research skills. What do you have to offer A PhD in neuroscience, psychology, computer science, or a related field; Peer-reviewed publications based
-
methods (e.g., PCA, PLS-DA, clustering, neural networks) to enable automated, polymer-specific classification. Optimize workflows for high-throughput imaging and real-world sample variability, minimizing