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-training that facilitate few-shot adaptations. The research will show how the complementarity of event-triggered learning and meta-learning can drastically increase RL efficiency at test time. The co-design
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design are often too slow, costly, and inefficient to cope with the increasing complexity of performance and resource-efficiency requirements. This collaborative doctoral project brings together
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interdisciplinary collaboration. That’s why our projects are designed specifically to connect diverse scientific fields and foster cross-institutional collaboration, enabling you to benefit from the combined
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Your Job: Digital methods for inverse materials design are essential to efficiently create new, sustainable and recycling-adapted structural metals. Alloys with a reduced number of elements, so
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climate states. Key responsibilities To carry out and complete your own research towards a doctoral degree. Design, run, and analyse equilibrium simulations with a coupled Earth-system model of intermediate
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academic records (including transcripts) at masters level or equivalent degree level. • Creative and innovation potential, ability to think out of the box. • Motivation of the candidate for inter
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engineering a strong background in digital design, hardware description languages (e.g. Verilog, VHDL, SystemC), reconfigurable architectures (e.g. FPGA, CGRA) What we expect from you: above-average degree
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Requirements: excellent university degree (master or comparable) in computer engineering or electrical engineering a strong background in digital design, hardware description languages (e.g. Verilog, VHDL
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responsibilities: To carry out and complete your own research towards a doctoral degree. Design, run, and analyse equilibrium simulations with a coupled Earth-system model of intermediate complexity to investigate
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from outside the University of Stuttgart Can attend courses and seminars specially designed for simulation technology Are able to exchange technical and methodical information Are integrated