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are currently focusing on organ bending during ovule growth, chirality establishment in plant tissues, cell wall mechanics and feedback between genetic signaling and mechano-sensing (for more background see Mosca
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Responsibilities Show excellent communication with the PI and laboratory personnel. Experience using standard bioinformatics tools, packages, algorithms, and databases to analyze high-throughput genetic, genomic
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: Among others, the following qualifications will be prioritised: Programming and algorithmic skills Experience in object-oriented programming Knowledge of .NET, HTML, CSS, JavaScript, and Bootstrap
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, inaccessible to standard techniques. To probe such regimes requires the development of fast and scalable algorithms for many-component systems, and of coarse-grained models that can be analyzed and simulated
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. Prototype autonomous systems for in-space manufacturing and testing. Develop AI algorithms for navigation, guidance, and control. Lead collaborative research proposals for NSF, DoD, DOE, NASA and with other
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connections to projects in which the CCA is involved (if relevant) Expertise in technical elements of computational astrophysics research, which may include but are not limited to: algorithm and software
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Our research The research focus of the Berg lab has been to combine quantitative approaches of mathematics and physics with experiments using electrophysiology, genetics, tissue clearing and other
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fundamental scientific principles with algorithmic innovations to empower discovery, understanding, and synthesis of materials with applications across critical societal domains – healthcare, manufacturing
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. Programming & Data Analytics (20%) Develop and implement algorithms for system identification, condition assessment, and structural health monitoring. Apply statistical and computational tools to assess
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theoretical and computational work is designed to integrate and abstract rapidly accumulating heterogeneous datasets, to propose critical tests of multiscale regulatory mechanisms, and to guide our own genetic