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implementations of massively distributed embedded systems that interact with each other and their environment to enable secure, goal-driven, autonomous and evolvable solutions. Project description E2PACKMAN is a
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distributed embedded systems that interact with each other and their environment to enable secure, goal-driven, autonomous and evolvable solutions. Project description E2PACKMAN is a €93.7 million European
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and constantly changing planet. To understand how this planet works, our researchers seek answers in the field, through laboratory experiments and advanced models. Our research and education cover a
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of software infrastructure to optimize data workflows Developing analytical methods to integrate different types of sequencing-based DNA data. Developing computational models for prognosis and treatment
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combine ultrafast pump–push–probe experiments with sub-10 fs resolution, finite-element simulations, and quantum models extending the Tavis–Cummings Hamiltonian. The aim is to demonstrate coherent control
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of engineered underground hydrogen storage in lined rock caverns (LRCs) excavated in hard crystalline rock. Your tasks are to: - develop coupled thermo-hydro-mechanical numerical models to simulate hydrogen
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laboratory tests, analysis of data, and modeling. Qualifications To be eligible, you must have a master’s degree in materials science or chemistry. You should have basic knowledge of building materials and be
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DDLS industrial PhD position We are announcing a position for a Data-Driven Life Science (DDLS) PhD student in data-driven precision medicine and diagnostics. To be a doctoral student means to
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journals. The tasks will include laboratory tests, analysis of data, and modeling. Qualifications To be eligible, you must have a master’s degree in materials science or chemistry. You should have basic
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-transporting ATPase SsZntA and the dopamine D2 receptor. Using laser-triggered caged compounds, you will initiate ATP- and ligand-driven reactions and follow the resulting structural changes from milliseconds