Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
cellular processes efficiently. This project aims at understanding the formation and functioning of aggregate-forming Archaea-Bacteria partnerships. The project involves working with syntrophic deep-sea
-
pipelines for joint analyses of imaging data from the Rubin Observatory’s LSST and NASA’s Roman Space Telescope. Appointment will initially be made initially for two (2) years, renewable upon mutual agreement
-
Labeling and Imaging“ Dr. Gražvydas Lukinavičius Am Fassberg 11 37077 Göttingen Germany www.mpinat.mpg.de/ Information pursuant to Article 13 DSGVO on the collection and processing of personal data during
-
environment for the pursuit of cutting-edge cardiovascular and metabolic research. We study the fundamental molecular, cellular, and physiological processes that underly normal and abnormal cardiovascular and
-
maintaining contacts with colleagues who can provide expertise and support in the analysis and interpretation of research findings. Key Responsibilities Develop computational pipelines for processing and
-
) Theoretical knowledge and practical experience in artificial intelligence-driven techniques for image processing Excellent proficiency of oral and written English in a scientific context Meriting criteria
-
. Collaborate on multidisciplinary projects involving high-throughput phenotyping platforms. Apply machine learning and deep learning techniques to improve image processing and trait prediction. Analyze large
-
well as access to sequencing facilities, high-end computer clusters, and an imaging and electron microscopy core facility. Research in our group covers diverse invertebrate lineages, with particular strengths in
-
-associated proteins. Collect and process cryo-EM data using the Talos Arctica and downstream pipelines (e.g., cryoSPARC and RELION). Integrate structural findings with biochemical and genetic data to define
-
demonstrated experience in computer vision or analysis of pathology images. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model