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SPM images of single molecules into their respective 3D molecular structures. Aim: Design, build, and test computer programs to interpret SPM images into 3D molecular structures. Fields: code
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methods (e.g. X-ray reflectivity, X-ray fluorescence) Design of cells and reactors for operando studies Coordination and execution of synchrotron beamtimes Collaboration with other groups, in particular
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
. The Department of Machine Learning for Materials Design is looking for a Postdoc (f/m/d): Machine Learning for Materials Modeling. Scope of Your Job In this role, you will contribute to ongoing research efforts in
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Max Planck Institute for Solid State Research, Stuttgart | Stuttgart, Baden W rttemberg | Germany | 2 months ago
program to detect and interpret SPM images of single molecules into their respective 3D molecular structures. Aim: Design, build, and test computer programs to interpret SPM images into 3D molecular
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interdisciplinary research. What will be your tasks? The position focuses on co-design and co-evaluation of recommendations for seagrass management and seagrass restoration on the basis of spatial analyses of its
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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
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of gender identity, disability, national origin, or any other demographic or personal factors. Your Profile: A Ph.D. degree in molecular or cancer biology A strong background in experimental design and
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Postdoc (f/m/d) Research Data Management and Data Visualization / Completed university studies (P...
Data Management and Data Visualization. Your tasks # Work with existing APIs for data access from various sources and design own APIs; combine different kinds of data such as sampled field data, geo
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both. Ideally, you bring strong technical expertise and the curiosity to work across modalities and domains. Your responsibilities Design and implement machine learning and deep learning pipelines
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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