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: Development and demonstration of 3D-in vitro environment for of electric field interference neuronal simulation with self-organized networked electrode array Project tasks and objectives: The BRAINET is an EU
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the European Union, in which we have 12 open positions for Doctoral Candidates (DCs). We aim to create a network of early-stage researchers equipped with knowledge and skills - including entrepreneurship –to develop
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Candidates (DCs). We aim to create a network of early-stage researchers equipped with knowledge and skills - including entrepreneurship –to develop and support implementation strategies that address
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the European Union, in which we have 12 open positions for Doctoral Candidates (DCs). We aim to create a network of early-stage researchers equipped with knowledge and skills - including entrepreneurship –to develop
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Candidates (DCs). We aim to create a network of early-stage researchers equipped with knowledge and skills - including entrepreneurship –to develop and support implementation strategies that address
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funded PhD positions, supervision by some of Europe’s leading researchers in this area, tailor-made career development plans, training in cutting-edge techniques, secondments, and collaborations with
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microbiological and geochemical data to develop diagnostic tools for assessing hydrogen potential and sustainability of geological hydrogen production. The position offers a unique opportunity to work in a
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ecology, and biodiversity research Motivation to work with complex ecological datasets and quantitative analyses Basic experience with statistical data analysis (e.g. in R) Interest in developing skills in
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and Communication Sciences . JOB DESCRIPTION The doctoral researchers at Tampere University will propose and develop novel deep learning methodologies, disseminate their results in high-quality
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bacteria increase antibiotics survivability, focusing on their gene networks. Our laboratory produces experimental data that will be analyzed by the student to study the bacterial gene network and develop