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information see (https://lundmark-lab.se/ ) Work responsibilities Culturing and analysing mammalian cell models for infection Designing and developing infection models of flavivirus and alphaviruses Generating
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Familiarity with performance modeling, analysis and optimization for heterogeneous architectures. Experience with developing code for: molecular dynamics, computational fluid dynamics, or quantum chemistry
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description Work on EU projects to develop next‑generation transport, emission and health forecasting models by integrating deep learning, xAI, and diverse data sources such as traffic sensors, smart‑card data
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overlooked but very promising component: grease-lubricated wheel bearing systems. The project aims to develop and implement a systematic and realistic method for evaluating new grease formulations, using a
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computational fracture mechanics. The experimental work involves developing new test geometries to study void nucleation under a wide range of stress states, using a combination of mechanical testing and advanced
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, solid state transformer, DC/DC converters, inverters, etc. Experience in modeling and stability analysis Experience in hardware development or real-time simulation. Awareness of diversity and equal
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develop the data-driven foresight methods to find out. About us At the Division of Physical Resource Theory, we study how societies can transition towards sustainability. Building on physics and systems
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but reuse a significant amount of code that has been built by 3rd parties. These code artifacts, in the form of externally developed libraries, packages, and frameworks form the core of their so-called
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are invasive or endangered in Northern Fennoscandia. The successful candidate will be responsible for laboratory work in this project, further developing the method for practical application to contexts in
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are often software-intensive and we develop mechanisms to create better software for safer, more secure, and more usable systems. You will be supervised by Associate Prof. Rebekka Wohlrab, whose research