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南方科技大学计算机系Pietro Oliveto课题组招收博士（人工智能方向）
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PhD in Time complexity Analysis of Bio-Inspired Computation and/or Theory-driven experimental Design Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China To apply for this position send your CV and academic transcripts of previous degrees in English to Prof. Pietro Oliveto at: olivetop@sustech.edu.cn Introduction Applications are invited for a fully-funded PhD studentship on the performance analysis of bio-inspired computation techniques such as evolutionary and genetic algorithms, are widely used heuristic search techniques at the heart of artificial intelligence. (Deadline to apply: 31 August 2026) About the project Bio-inspired meta-heuristics, such as evolutionary algorithms, genetic algorithms or artificial immune systems are general purpose algorithms that mimic powerful mechanisms from nature such as the natural evolution of species or the collective intelligence of animals with the goal of solving complex optimisation problems. They have been applied successfully to a broad range of problems in various disciplines with remarkable success. They are particularly useful in settings where limited knowledge about the problem is available (black-box optimisation) and evaluating candidate solutions is the only means of learning about the problem at hand. In recent years theoretical analyses have emerged that provide mathematically proven statements regarding the performance of bio-inspired algorithms. They rigorously estimate the expected time required by the algorithms to find a satisfactory solution for various optimisation problems. Such analyses use mathematical techniques drawn and extended from the fields of randomised algorithms, probability theory and computational complexity. The results allow for insights into the working principles of bio-inspired meta-heuristics, enable the assessment of parameter choices and design aspects, and ultimately guide towards the design of more powerful algorithms. This studentship offers a valuable opportunity to work within this very active, challenging and exciting field of research at the intersection between theoretical computer science and artificial intelligence. The successful applicant will perform high quality research in the area of either time complexity analysis or experimental theory-driven design at the interface between bio-inspired computation and artificial intelligence. During the PhD studies, he/she will develop expertise in one or more promising research areas of his/her choice in this wide research area. Possible topics include the performance analysis of: a) Population-based meta-heuristics: highlighting their advantages over single-trajectory algorithms and/or the advantages of recombination over mutation-only algorithms; b) Algorithm configurators: how to evolve the optimal parameter settings for the meta-heuristic; c) Hyper-heuristics: how to evolve the meta-heuristic itself; d) Genetic programming: how to evolve computer programs effectively. About the University/Department Established in 2010 with the mission to reform Chinese tertiary education and become a top-notch international research university, SUSTech was launched in the tech capital city of Shenzhen. SUSTech is becoming the important epicentre for China’s science and technology academic research and for the cultivation of innovative minds. The rapid ascent of SUSTech onto the global stage is remarkable. In the Times Higher Education (THE) World university Rankings 2023, it ranked 8th in Mainland China and 166th among the universities in the world. In THE Young Universities Rankings 2024, SUSTech was ranked 1st in China. The SUSTech campus sits in the rolling hills of Nanshan District, with the verdant green lawns reflecting the environmentally friendly policies of the university. The natural and tranquil environment combines perfectly with the modern style of Shenzhen and its convenient location. With the campus covering an area of nearly 2 square kilometers, there is plenty of room for students to cogitate and consider their research or relax and enjoy their lives on campus. With students transiting the campus on foot, by bike or utilizing our convenient electric shuttle buses, its commitment to environmental sustainability is strong. Located in the dynamic metropolis of Shenzhen, China’s Silicon Valley, SUSTech is centered on a thriving ecosystem of entrepreneurship, innovation and research. Some 43 per cent of the total PCT patent applications in China came from Shenzhen in 2017, and the city shows no signs of slowing down. As China’s research and development center, it is the perfect place for entrepreneurs, researchers and innovators alike to make their home alongside tech giants such as Huawei, Tencent, BYD, DJI, BJI and Mindray. Shenzhen is also only distant 17 minutes from Hong Kong city centre by high speed train and about an hour from Macau by ferry. The successful candidate will join the recently established AI-Theory Lab in the department of Computer Science and Engineering with world-leading expertise in bio-inspired computation. Candidate Requirements Applicants must have recently completed a Masters degree in Computer Science or close to completion. Outstanding applicants from Mathematics are also encouraged to apply. The successful applicant must have excellent analytical and computational skills. He/She must be an excellent team player who can work independently and communicate well with others. If English is not their first language, they must have English language qualification. This position is open to all qualified candidates independent of nationality. Funding and Eligibility This studentship provides stipend per annum for four years. Funding is available for conference attendance and collaborative research visits to related organizations world-wide. The AI-Theory Lab at SUSTech maintains effective collaborations with all the research organisations with major expertise in the theory of bio-inspired computation world-wide. Supervisor Bio Professor Pietro S. Oliveto is Chair of the AI-Theory Lab at SUSTech. His main research interest is the rigorous performance analysis of bio-inspired computation techniques. He has successfully supervised PhD projects on the theoretical foundations of evolutionary computation, artificial immune systems, hyper-heuristics and automatic algorithm configurators. To apply for this position send your CV and academic transcripts of previous degrees in English to Prof. Pietro Oliveto at: olivetop@sustech.edu.cn Webpages: https://www.sustech.edu.cn/en/faculties/pietrooliveto.html https://peteroliveto.github.io/ Key Words: Bio-inspired computation, theory, randomized search heuristics, evolutionary optimization. |
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