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methods, including modern machine learning methods, to draw inferences from register data. A third project “Integrative machine and deep learning models for predictive analysis in complex disease areas“ is
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spectroscopies, as well as molecular biology for introducing site specific alterations. Atomic level structural insight will be obtained via single particle analysis cryo-EM and snapshot serial crystallography
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for carbohydrate, lipid or protein analyses. Skills in computational biology or biological modelling. Experience working with cell walls from plants or other organisms. Be proactive and take own initiative
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To possess basic eligibility, the applicant should hold an advanced degree, have completed studies equivalent to at least 240 higher education credits, at least 60 of which at an advanced level, or in
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to effectively compile linear algebra expressions when the matrix sizes are unknown at compile-time. The project aims to address the problem using e-graphs. An e-graph is a data structure commonly used in
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requirements. General eligibility is granted to those who have completed a second-cycle (advanced level) degree, fulfilled course requirements of at least 240 higher education credits (ECTS), of which at least
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admitted to doctoral studies in sociology, applicants must meet both the general and specific entry requirements. General eligibility is granted to those who have completed a second-cycle (advanced level
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: detailed theoretical studies and optimization of light guidance in HCFs, characterization of fabricated HCFs (on both structural and optical transmission properties), experimental investigations of material
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systems. Advanced programming skills. Academic writing skills and the ability to typeset papers in LaTeX. It is highly meritorious if you enjoy working with math notation and formal proofs. Alternatively