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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | about 2 months ago
chromatographic purification. Crystallization and precipitation are alternative purification techniques that operate at substantially lower costs, but their process design and optimization is challenging due
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on the basis of the following criteria: Technical competencies Strong ability to design and optimize integrated optic devices, model their optical, optoelectronic, thermal-optical properties using commercial and
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exoplanets, including numerous water world candidates. This project will focus on analysing JWST datasets to identify and characterise the atmospheric properties of water worlds. Key objectives Analyse JWST
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/research/air-water-and-landscape-science ). Duties The PhD project will focus on uncertainty quantification in modelling flow and solute transport in fractured rocks. The work will include numerical
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working environment numerous possibilities of career development and advancement cooperation with international partners (extensive network of Erasmus+ partner institutions) canteen, allowance for meals
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confidence in the measurements and establish traceable validation routes. Optimize the methods for realistic converter operating conditions and communicate practical guidance to academic and industrial users
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with a strong background in applied mathematics, control theory and/or optimization to apply for a fully funded 4-year PhD position in the Smart Manufacturing Systems (SMS) group at the Engineering and
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the development of numerical methods for astorphysical fluid dynamics and radiation transport. Projects may employ a range of approaches from analytic modelling and numerical calculations on desktop
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methods and GIS tools to create 3D environments that integrate high-resolution 3D urban models with climate-resilience objectives. This should help policymakers and citizens optimize energy-efficiency
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doctorate, contains: Artificial Neural Networks and Large Language Models offer state-of-the-art performance at numerous AI tasks, but being black boxes, they lack explainability which makes them difficult