Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Nature Careers
- Leibniz
- Technical University of Munich
- Forschungszentrum Jülich
- Heidelberg University
- University of Tübingen
- Fraunhofer-Gesellschaft
- Fritz Haber Institute of the Max Planck Society, Berlin
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- ; Technical University of Denmark
- DAAD
- Free University of Berlin
- Max Planck Institute for Biology Tübingen, Tübingen
- Max Planck Institute for Human Development, Berlin
- Max Planck Institute for Molecular Biomedicine, Münster
- Max Planck Institute for Sustainable Materials GmbH, Düsseldorf
- Max Planck Institute for the Structure and Dynamics of Matter, Hamburg
- University of Greifswald
- WIAS Berlin
- 9 more »
- « less
-
Field
-
plan and capital-forming payments 30 days of vacation per year Flexible working hours Possibility of mobile work and part-time work Family-friendly working environment Sustainable travel to work
-
learning and signal processing approaches to classify cap types from raw signal traces. Collaborate closely with experimental researchers to guide experimental design and interpret data. Contribute
-
Your Job: We are seeking highly motivated postdoctoral researchers to join these projects. If you are passionate about protein dynamics and design, protein function prediction, small molecule
-
functionalities (GUI and web-service) Participate in field work organization, sampling plan establishment and in-situ data acquisition Your Profile PhD in environmental sciences or computer science, with a proven
-
-tracking technology, Computer Vision, Speech/ Language Processing, VR, and AR. • Know-how/Interest in designing user studies. • Excellent communication skills and a collaborative spirit to work with
-
assistants Your profile: PhD in social, I/O, or experimental psychology experienced in experimental research Interest in designing online interventions Profound knowledge of English Please contact Prof. Dr
-
hearing loss. However, current neural devices are large, complex, and invasive, and are therefore used by only a fraction of people who could benefit from them. The goal of NANeurO is to design new
-
team to work on machine learning-supported rapeseed genomics and breeding. Your tasks: You design, train and interpret deep-learning models to predict regulatory gene variants in rapeseed genomes. You
-
organoid and assembloid formation can be controlled via microfluidics and how the assembloid-designs affect cell biology. The position will be embedded in the two research groups of Dr. Kai Melde
-
multidisciplinary team to design and carry out experiments with infants with neurodevelopmental disorders Analyze and interpret complex behavioural and audio-visual data Dissemination of scientific results and lead