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Field
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Description Are you excited about using large-scale AI to accelerate scientific discovery? Join a Horizon Europe project developing next-generation scientific foundation models that combine knowledge graphs
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 9 days ago
the replicator equation. The candidate(s) may also be required to develop computational and algorithmic platforms to link models to biological data. The project integrates dynamical systems, graph theory, linear
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good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience with large-scale
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We invite you to apply for a 2-year postdoctoral position in the area of hybrid AI, combining modern language models (LMs) with ontologies and knowledge graphs (KGs). The position is part of a newly
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
independently, has a passion for AI and its applications, and is willing to learn new technologies. The candidate should have a PhD in Computer Science or a closely related field. Relevant background and skills
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prediction of gene perturbation effects for drug discovery. The successful candidate will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural
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data for European and international funding applications. Specific Requirements PhD in Physics, Engineering, Mathematics, Computing, Bioinformatics or related fields. Master's degree in Data Science
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candidate is self-motivated and hard-working with a PhD in Data Science, Computational Social Science, Computer Science, or Information Science, with no more than five years post receipt of the PhD
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several major types of mobility modeling, with the aim of improving their respective efficiency and usage: four-step models, multi-agent systems and a mobility model developed in the PhD thesis of Louisette
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. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness