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Knowledge and experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl
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together with a PhD student in the lab of Prof. Jeroen Krijgsveld, which will focus on the proteomics part of the joint SFB/CRC project applying state-of-the-art proteomic approaches, e.g. low-input/single
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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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candidate will be enrolled in one of the general degree programs at DTU. For information about our enrolment requirements and the general planning of the PhD study program, please see DTU's rules for the PhD
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. The PhD student will work under the supervision of Prof. Voets and in close collaboration with Prof. Wouter Everaerts from UZ Leuven’s urology department. The research team has a strong track record in
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Your Job: You will work in the Electrocatalytic Interface Engineering department, which is headed by Prof. Dr.-Ing. Simon Thiele. The department focuses on the fabrication, analysis and simulation
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will include data acquisition, analysis, and interpretation, as well as collaboration with clinicians for human tissue studies. The candidate holds a Master degree in biomedical sciences, medicine
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PhD project is encouraged. The successful candidate will be affiliated with the Institute for Research on Socio-Economic Inequality within the Department of Social Sciences in the team of Prof. Dr. Anja
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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission