142 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions in Sweden
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leap in the battery development is expected to be lithium solid-state batteries (SSB), allowing the replacement of the flammable organic electrolyte in Li-ion batteries with a safer and a more compact
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samples, lack of training data and sample variability. In this project we aim to develop AI/ML workflows for improved quantitative analysis of LNPs. Your responsibilities will include optimisation of data
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molecular biology. Data-driven Life Science Fellows program AlphaCell is a new SciLifeLab initiative aimed at building the first molecular-level computational model of the human cell. The program is led by
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expertise. Are scientifically curious, independently driven, and motivated by biologically meaningful modelling problems. Have good teaching abilities. Have awareness of diversity and equal opportunity issues
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Energy Science aims to identify, analyse and describe the major environmental challenges of our time, with the aim of developing models, tools and competitive technological solutions to support the
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humanoid robot control methods – including reinforcement learning and whole-body MPC – to model human balance and step recovery in urban transport scenarios. Develop and validate a parameterized human model
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constellation of SciLifeLab researchers and infrastructure units. This position is embedded in Avlant Nilsson’s research group at Karolinska Institutet and SciLifeLab. Our lab develops deep learning models
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group has for many years conducted research on the ICF and its application in developmental, psychiatric and somatic conditions. The research aims to develop and evaluate ICF-based models, assessment
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.): Research within hydrometallurgy, redox–dissolution chemistry, battery recycling, and data-driven modelling Develop and apply mechanistic and data-driven models to identify reaction regimes and predict
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of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven