43 parallel-programming-"DIFFER"-"Mohammed-VI-Polytechnic-University" positions at SciLifeLab in Sweden
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with different backgrounds, experiences and perspectives – diversity enriches our work and helps us grow. Preserving everybody’s equal value, rights and opportunities is a natural part of who we
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sinks, recent research has shown that they can also emit methane, nitrous oxide, and underexplored VOCs. Microbial activity is key to these emissions, but we need to understand how different processes
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will be financial coordination of the newly launched KAW funded SciLifeLab Alpha Cell program as well as the EU MSCA SciLifeLab PULSE Post Doc program PULSE Postdoc program. About the Programs The Alpha
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and accepted to the PhD program at Stockholm University. Project description Project title: “Deep learning modeling of spatial biology data for expression profile-based drug repurposing”. A new exciting
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year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
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processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data Driven Life Science (DDLS) aims to recruit and train the next generation of data driven life scientists
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areas, such as scientific and educational development, leadership development as well as patent and innovation support. The position is part of the SciLifeLab Fellows program and will be placed within
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stakeholders at all SciLifeLab sites in Sweden, e.g. representing the technology platforms, the national data centre, the operations office, the training hub, the data-driven life science (DDLS) research program
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and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create globally leading computational and data
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to build sequence dependent predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming