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About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with
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world networks have a multidimensional nature such as networks that contain multiple connections. For instance, transport networks in a country when considering different means of transportation
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activities. Your Profile: Master and PhD degree in astronomy, physics, computer science or equivalent fields of study. Proven experience in N-body simulations and the comparison of simulation and observation
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network of collaborators Other valued appreciated: autonomous, proactive, focused on the research program, deliver on time Languages: English Benefits package Subsidized meals Partial reimbursement
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working at the boundaries of several research domains PhD degree in computational biology, bioinformatics, systems biology, bioengineering, chemical engineering, or a related discipline Knowledge and
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.) if candidate holds a relevant degree and is working on PhD/DPhil) together with established knowledge in wired computer networks and sustainable computing, significant coding experience (both Python and C/C
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funded by UKRI EPSRC and is fixed term for 12 months. You will be contributing to joint UKRI EPSRC – NSF CBET project on sustainable computer networks, with a focus on carbon emissions reduction and
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of the ice sheet surface including firn, and maintains a dedicated network of automatic weather stations. Currently, our research group has 5 staff members, 7 Postdocs and 5 PhD candidates. Within this team, 2
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Lomet, Research Engineer in AI at LIAD, CEA Saclay · Marianne Clausel (University of Lorraine), scientific lead of the national PEPR causali-t-ai program, · Myriam Tami, Associate Professor
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental