20 parallel-computing-numerical-methods-"DTU" Postdoctoral positions at Nature Careers in Sweden
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, visualization, and development of new computational methods for processing and analysis of large-scale omics data. We welcome applications from candidates with pure computational background and those combining
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Postdoctoral studies in single-cell and computational biology Do you want to contribute to top quality medical research? A postdoctoral position is available in the laboratory of Professor Francois
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), numerical methods, and basic knowledge of material science. It is meriting to have one or more of the following skills/qualities: experience and/or thorough understanding of theoretical/numerical methods
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numerical methods used to design wind turbines and understand turbulent combustion in jet engines, this research aims to address critical computational challenges in simulating the physical dynamics
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extensive cell tracking studies with massive parallel sequencing and molecular manipulations to gain insights into regulatory mechanisms whose appropriate targeting could impose regenerative traits to mammals
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Postdoctoral position in fabrication of hollow-core optical fibers for next-generation communication
, both in oral and written forms. Highly meritorious: Knowledge in theoretical/numerical methods for simulation of thermo- and fluid dynamics. Knowledge in optics. Ability to communicate in Swedish. We
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new method for lncRNA gene identification from whole genome sequences. Collaborating with experimental researchers to integrate computational findings/tools with functional investigation. Scientific
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photoreceptive pathways using mouse as a model system. Methods used in the lab include various in vitro, ex vivo and in vivo approaches, as well as functional and behavioral studies of relevant opsin knockout mice
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? With data-driven methods, new opportunities arise to understand ecosystems as complex, dynamic networks. This project aims to analyse the world’s most extensive eDNA database, consisting of weekly
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The Rantalainen group is focused on application of machine learning and AI for development and validation of predictive models for cancer precision medicine, with a particular focus computational pathology. Our