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performance computing numerical methods in our state-of-the-art open source micromagnetic model, MagTense. MagTense is based on a core implemented in the Fortran programming language, and it relies
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and documenting reproducible analyses and workflows Excellent English skills written and spoken Desirable experience and skills: Training in statistical methods appropriate for single-cell biological
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fabrication methods (robotics) while integrating real-time lifecycle data into decision-making that substantially reduces the construction phase’s environmental impact. The selected candidate will work on DTs
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bacteria, including E. coli. Experience with investigating protein folding of complex proteins. Development of synthetic biology tools for modularizing genetic elements to facilitate efficient cloning and
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Experience with and motivation for establishing new methods A PhD in life sciences or related An excellent research and publication track record Excellent English skills, written and spoken Desirable
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practical experience with various advanced polyolefins’ pretreatment methods (advanced chemical oxidation, UVc, ozone, plasma treatment, etc.), which will be used to improve degradability of the substrate. We
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upstream regulator of epigenetic and transcriptional reprograming underlying EMT. Nature Communication. Aug 2017. Dynamics and function of distal regulatory elements during neurogenesis and neuroplasticity
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quantitative behavior genetic methods to explore the association between neighborhood characteristics and various developmental outcomes. Outcomes we will explore include education, conduct problems, and mental
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at the intersection of advanced probabilistic machine learning and microbial bioscience. This position offers a unique opportunity for developing novel probabilistic ML methods with a view towards
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machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and