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and enthusiastic individual who meets the following criteria: Recently earned a Ph.D. in bioinformatics, computational biology, computer science, electrical and computer engineering, or a related
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. Antonio Scialdone’s group at Helmholtz Munich, a leading European hub for AI in biology. The successful candidate will design and implement physics-informed machine learning frameworks and predictive models
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from different fields: AI (machine learning, big database, etc) Semiconductors
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We are recruiting a group of postdocs who are eager to pursue ground-breaking biomedical research, and we will help them to establish themselves as future scientific leaders. This postdoc program is
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analysis or habitat monitoring Highly valued: Experience applying AI or machine learning methods to remote sensing data Experience with drone-based point cloud collection Experience working with or advising
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methodology. Applying AI and machine learning (ML) tools (including Python, R, and possibly other languages) to test and evaluate biomedical hypotheses. Developing benchmarks and working together with staff
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data analysis is required. The lab mostly uses R for data analyses; knowledge of R is not required, and the postdoctoral scholar will have the opportunity for mentorship and learning. To Apply: Motivated
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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imaging, deep proteomics, metabolomics, metaproteomics, and machine learning (ML) approaches to develop diagnostic classifiers, spatial tissue atlases, and identify potential therapeutic targets