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measurements, vegetation inventory and biodiversity assessments for a set of diverse continuous cover forestry systems in boreal Sweden. The project will develop bottom-up estimates of the forest ecosystem
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for foreign researchers who place their qualifications in Sweden. Duties and profile This postdoctoral project is focused on applied AI-based computer vision and precision cancer medicine research centered
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(AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians working collaboratively. Our focus is on developing practical methods that blend traditional disciplines
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initiative to develop a quantum computer based on superconducting circuits. Part of the project is also to solve specific problems related to this goal. A key challenge in this effort is mitigating errors in
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applied machine learning projects in, e.g., computer vision, in close collaboration with industry partners. The position is not connected to an existing project, so the postdoc fellow will either join an
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. Demonstrated skills in Python programming, or other computer programming. Strong interest in data science, such as data collection and curation, modelling. Excellent written and oral English communication skills
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excellent skills in modern computer programming languages such as C++, Python, MATLAB or R. We look for candidates who enjoy collaborating in interdisciplinary teams and are good at communicating science in
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for the position are: It is meritorius if you have solid experience with the following computer programs: CryoSPARC, Phenix, Coot, Chimera and Pymol, It is meritorius if you have experience working with eukaryotic
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of the Wallenberg Centre for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing
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estimates remain highly uncertain because existing approaches often neglect critical lake-specific dynamics and feedback mechanisms that are essential for accurately predicting ecological responses and