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and/or application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Tasks The tasks include primarily leading and conducting research
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for an excellent young life science or computational researcher to become Group Leader. Fellowships are targeted towards applicants to start their first independent group within a few years of their PhD. We offer
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into consideration. We are seeking applicants who have a PhD degree in machine learning, statistics, scientific computing, computational chemistry, applied mathematics, or a related area that is considered relevant
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for an excellent young life science or computational researcher to become Group Leader. Fellowships are targeted towards applicants to start their first independent group within a few years of their PhD. We offer
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passive and active flow control algorithms, potentially incorporating machine learning/AI, to enhance aerodynamic performance and stall delay with rapid response times. The research is conducted in
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well as Hi-C and transcriptome sequencing. You will use these datasets to detect chromosomal abnormalities and study their breakpoints. Using statistical methods and machine learning, we will explore how
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of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and
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-constrained models. Currently, we are advancing the development of single-cell models, machine learning approaches based on cultivation data, and the integration of metabolic models with computational fluid
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parental leave, sick leave or military service. The following experience will strengthen your application: Experimental atomic physics Optics Photonics Optomechanics Nanofabrication Nanomechanics Cryogenics
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of the work will be based on the data reduction framework scipp (https://scipp.github.io ). Requirements Applicants must hold a PhD in physics, materials, computational science, or a similar area of science and