卢森堡大学PhD position: Beyond 5G/6G Wireless Communications Technologies (M/F)申请条件要求-申请方
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卢森堡大学
PhD直招介绍
The University of Luxembourg is a multilingual, international research University.
The University of Luxembourg is continuously seeking to hire highly motivated and outstanding doctoral researchers to work on different enabling technologies for the next generation (Beyond 5G/6G) wireless communications networks for its Interdisciplinary Centre of Security and Trust (SnT), within the Signal Processing and Communications (SigCom) research group, led by Prof. Björn Ottersten and Prof. Symeon Chatzinotas.
The SigCom research group at the SnT carries out research activities in the areas of signal processing for wireless communication systems including satellite communications and radar systems, and is rapidly expanding its research areas to various enabling technologies for beyond 5G/6G wireless networks. For details, you may refer to the following: https://wwwen.uni.lu/snt/research/sigcom .
Doctoral candidate (PhD student) in Beyond 5G/6G Wireless Communications Technologies (M/F)
· Fixed-term contract up to 3 years in total, pending satisfaction of progress milestones (CDD), on full time basis (40 hrs/week)
· Employee and student status
· Number of positions: Many
· Deadline: Until filled
Your Role
The successful candidate is expected to perform the following tasks:
· Carrying out novel research works in one of the following predefined areas
· Novel communications technologies for Beyond 5G/6G networks and services
· Cellular, UAV, IoT, Tactile Internet, MEC, V2X, D2D, M2M, eMBB, mMTC and URLLC
· Machine learning/deep learning techniques and Artificial Intelligence for wireless communications
· Reinforcement learning, active learning, transfer learning, federated learning and interpretable/explainable AI
· Software defined networking, network virtualization and network slicing for wireless networks
· Energy-efficient communication technologies
· Energy harvesting, SWIPT, backscatter communications and reconfigurable intelligent surfaces
· Advanced multi-antenna technologies for B5G/6G wireless networks
· Massive MIMO, cell-free massive MIMO, beamspace massive MIMO, active antennas, smart antennas, precoding, hybrid analog-digital beamforming and 3D beamforming
· Communications technologies at the higher frequencies
· mmWave, TeraHertz and optical
· Communication technologies for Tactile Internet applications including wireless augmented/virtual reality and teleoperation systems
· Quantum-assisted communication technologies for 6G wireless networks
· Disseminating results through scientific publications
· Presenting results in the well-known international conferences and workshops
卢森堡大学 PhD position: Beyond 5G/6G Wireless Communications Technologies (M/F)项目有没有奖学金，是不是全奖Phd招生，下面我们一起看一下【大学名称】Phd的奖学金资助情况
项目资助情况
The University offers a Ph.D. study program with a Fixed Term Contract up to 3 years in total, pending satisfaction of progress milestones (CDD), full-time (40 hrs/week). The University offers highly competitive salaries and is an equal opportunity employer.
卢森堡大学Phd申请条件和要求都有哪些？PhD position: Beyond 5G/6G Wireless Communications Technologies (M/F)项目是不是全奖？有没有奖学金？下面我们一起看一下卢森堡大学申请Phd直招需要具备哪些条件和要求，以及托福、雅思语言成绩要到多少才能申请。
申请要求
The candidate should possess an M.Sc./M.Eng. Degree in Telecommunication Engineering, signal processing, machine learning or a closely related field in Electronic, Electrical and Computer Engineering.
The ideal candidate should have been within top 10% of class during his/her graduation, and should have published at least one authored conference paper in an international conference or one authored journal paper in an international journal.
Experience: The candidate should have some knowledge and experience in some of the following topics/tools:
· 5G wireless communications technologies
· Wireless Internet of Things (IoT) technologies
· Unmanned Aerial Vehicles (UAVs)
· Resource allocation and optimization
· Network virtualization and network slicing
· MAC techniques/protocols for wireless systems
· Graph signal processing
· Machine learning (supervised, unsupervised and reinforcement) and tools (TensorFlow, PyTorch, Keras and GreyCat)
· Deep learning (deep neural network, recurrent neural network, LSTM)
· Optimization theory
· Stochastic geometry
Programming skills: MATLAB, Python or C++.
Language Skills: Fluent written and verbal communication skills in English are mandatory.
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