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- Leibniz-Institute for Plant Genetics and Crop Plant Research
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research fields including anatomy, physiology, genetics, biochemistry, microbiology, and pathology. The DBMS main areas of interest are: Experimental and Applied Biology, Chronic Degenerative Diseases, and
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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | 8 days ago
21 Aug 2025 Job Information Organisation/Company Leibniz-Institute for Plant Genetics and Crop Plant Research Research Field Agricultural sciences » Agronomics Agricultural sciences » Other
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. Knowledge on multiphase (gas-particle two phase system), thermal energy storage, and/or renewable hydrogen technologies. Familiar with application of machine learning and deep learning algorithms to fluid and
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· developong new genetic algorithms related to finite element (FE) modeling · presentation of results and their disseminatio The successful candidates must be enrolled in PhD School program
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microenvironment structures are associated with genomic features and clinical outcome. Danenberg E et al. Nat Genet. 2022 May;54(5):660-669. doi: 10.1038/s41588-022-01041-y Imaging mass cytometry and multiplatform
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Bioinformatics, Computational Biology, Computer Science, Biomedical Engineering, Computer Engineering, Genetics/Genomics or related field experience with ‘omics platform output experience with biological datasets
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The Quantitative Genetics research group is interested in developing statistical genomics toolboxes to decipher the genetic architecture of important crop traits like grain yield heterosis. In
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theoretical research is focused on embodied neuroAI, recognising that the body influences biological neural networks, the continuity of actions, and sensory inputs. Leveraging advancements in Drosophila genetic
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analysis, with possible specialisations in genomic and molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. This is based on perspective and
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molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. Importantly, mastery of the experimental and theoretical aspects shall equip doctoral