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瑞典皇家理工学院多个人工智能、机器人、可持续复合材料博士奖学金位置
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本文来源于：博士博后科研工作助手 公众号 https://mp.weixin.qq.com/s?__biz ... p;amp;lang=zh_CN#rd 皇家理工学院（英文：KTH Royal Institute of Technology，简称：KTH）成立于1827年，坐落于瑞典王国首都斯德哥尔摩，是瑞典国内规模最大、历史最悠久的理工院校，为北欧五校联盟成员之一。世界百强名校。 KTH强大的研究声誉巩固了该校作为欧洲最著名的技术大学之一的地位，与欧洲大陆其他理工院校一样，不设置综合院校的文、法、医等学院，只专注于工程与技术领域的人才培养与科学研究。 根据2022QS世界工程技术院校排名，KTH位列世界第28位，欧洲大陆第8位。其中细分学科全球排名：石油工程（21）、建筑学（22）、电子电气工程（23）、机械与航空航天工程（26）、材料科学（27）、土木工程（44）、计算机科学与信息系统（54）、数学（59）、统计与运筹学（51-100）。 KTH位列2022QS世界大学排名第89位 ，2022QS毕业生就业竞争力排名第70位。 PhD position 1: Doctoral student in large-scale distributed machine learning With the development of computing and communication technologies, and emerging data-driven applications, e.g., IoT based intelligent systems, social network analysis and vehicular networks, the volume of data for various learning systems increases explosively along with the number of involving computing nodes. Thus, large-scale distributed machine learning (e.g., federated learning, and alternating direction method of multipliers (ADMM)) has been pervasive in our societies and industries. However, the practical performance of DML is often limited by various bottlenecks and is still far from theoretical upper limits. Thus, this project will develop efficient algorithms and schemes to achieve reliable, secure and low-complexity large-scale DML. One key approach is to exploit network and channel coding schemes. Theoretical analysis will be performed using learning and communication tools (e.g., graph model, coding and information theory, optimization). The result will also be verified by simulations with true data. Deadline : 15.Aug.2022 Apply website: https://www.kth.se/en/om/work-at ... job/where:4/apply:1 PhD position 2: Doctoral student Deep Learning for sequential and graph data The PhD thesis will focus on state of the art Graph Neural Network Methods and search for advancements in the areas of explainability, interpretability and other fundamental aspects. It will also deal with application of the above methods to real world problems in NLP, sequences, time series, images and social network data. The prior work of the supervisor will support further achievements in this field. Deadline : 08.Jul.2022 Apply website: https://www.kth.se/en/om/work-at ... job/where:4/apply:1 PhD position 3: Doctoral students in Networked Systems for Machine Learning Your work will entail design, implementation, and evaluation of distributed systems and networks for building ultra-low latency Internet services. Special emphasis will be paid to low latency, resilient frameworks for machine learning (including distributed and federated learning). Examples of other services to be built include advanced highly streamlined server software, Network Functions Virtualization (NFV) chains at the true speed of the underlying hardware, intra datacenter loadbalancing, agile and efficient geo-distributed data storage systems. Deadline : 17.Aug.2022 Apply website: https://www.kth.se/en/om/work-at ... job/where:4/apply:1 PhD position 4: “Ph.D. student in AI for link-layer efficient in wireless communications The doctoral project is part of a larger project on artificial intelligence (AI) for Wireless Communications, with funding from the Swedish Foundation for Strategic Research (SSF). The project brings together researchers from KTH, Chalmers and Ericsson Research, who will address several aspects of AI in and for wireless communication systems at different system levels. The currently advertised position will focus on the use of AI and machine learning for improved efficiently in the physical and link-layer. The doctoral program in Electrical Engineering provides world-class quality education, including a large list of graduate courses, enabling the development of relevant competencies and skills. Deadline : 15.Aug.2022 Apply website: https://www.kth.se/en/om/work-at ... job/where:4/apply:1 PhD position 5: Doctoral student in robotics and perception In this project we study mapping for robotics. The vision is a 3D grid representation maintained in real-time and capable of modeling a dynamic scene, including the moving objects. We will extend our work on UFOMap, which already provides an efficient way to manage data such as, e.g., occupancy and semantics. Some questions to address: How to model the dynamic information and incorporate measurements of this from various sources (optical flow, object trackers, etc)? How to enable predictions of future states? How to model the strong correlation between voxels but which is ignored in the standard grid formulation? Deadline : 15.Aug.2022 Apply website: https://www.kth.se/en/om/work-at ... job/where:4/apply:1 PhD position 6: Doctoral student in data-driven geometric methods for robotics In this project, we will develop simplicial complex-based robot configuration space models for embodiment-aware robot motion planning and learning from demonstration. We will develop extremely large scale and detailed data-driven simplicial complex-based models of robot arm configuration spaces that represent the complex geometry that they exhibit. Based upon these representations we will develop algorithms for efficient updates, optimal motion planning and probabilistic reasoning for robotic manipulation. The project will be highly interdisciplinary as it lies at the intersection of Computational Geometry, Motion Planning, Bayesian Machine Learning and Optimal Control. Deadline : 08.Aug.2022 Apply website: https://www.kth.se/en/om/work-at ... job/where:4/apply:1 PhD position 7: Doctoral student (lic) Bio-based composite materials for sustainable roads We are looking for a doctoral student for a licentiate in highway engineering. In the project, we want to investigate the applicability of lignin in asphalt. Our target is to study lignin-modified asphalt mixtures through a synergetic combination of 3D imaging techniques, based upon X-ray and neutron radiation sources, multi-scale chemo-mechanical testing, and computational modelling. The work is carried out in close collaboration with several partners in Europe and requires very good ability to work independently. Tests campaigns in several facilities will be carried out (Lund University in Sweden, ILL in France, PSI in Switzerland). Deadline : 01.Sep.2022 Apply website: https://www.kth.se/en/om/work-at ... job/where:4/apply:1 本文来源于“博士博后科研工作助手”（微信公众号），该公众号会定期更新海内外博士、博士后工作和科学研究信息。亲测很不错哦，有需求的朋友，可以关注。（如有侵权，请私信删除，谢谢） |
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