[Job-offers-cs] Research Fellow Position available in Time Complexity of Bio-inspired Computation @ SUSTech, Shenzhen, China

[Pekka Orponen]

Time complexity Analysis of Bio-Inspired Computation

Department of Computer Science and Engineering, Southern University of 
Science and Technology (SUSTech), Shenzhen, China


Introduction

Applications are invited for a fully-funded Research Fellow in the time 
complexity analysis of bio-inspired computation techniques such as 
evolutionary algorithms,  genetic algorithms, artificial immune 
systems which are widely used heuristic search techniques at the heart 
of artificial intelligence.


About the project

Bio-inspired meta-heuristics are general-purpose optimization paradigms 
that draw inspiration from biological systems Popular examples include 
evolutionary algorithms, genetic algorithms and artificial immune 
systems. The AI-Theory Lab works towards providing a theoretical 
foundation for understanding the working principles of these heuristic 
algorithms by quantifying how quickly they find satisfactory solutions 
for various problems, thus explaining when and why they are efficient. 
This understanding exposes how performance depends on algorithmic 
parameters, enables informed choices as to when to use what kind of 
heuristic and allows the design of better bio-inspired algorithms. 

The aim of the project is to develop the mathematical methodology for 
explaining and predicting the performance of bio-inspired search 
heuristics. The methodology will be used to derive and extend the 
theoretical foundations of bio-inspired computation.

Selected topics include the performance analysis of:

a) Population-based search 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;


Person Specification

- PhD in computer science (or close to completion) or closely related area

- Expertise in some or all of the following:

- Theory of bio-inspired computation

- Algorithm time complexity analysis and computational complexity

- Computational complexity analysis of randomized algorithms

- Analysis of stochastic processes

- Excellent computer programming skills (JAVA, C)

- Publication record commensurate with career stage in high impact 
journals and conference proceedings

- Experience of Latex, SVN, GIT or analogue



Main Duties and Responsibilities


- Contribute to the development of mathematical techniques for the time 
complexity of bio-inspired optimization heuristics

- Perform runtime analyses of bio-inspired search heuristics for 
combinatorial optimisation problems

- Investigate the impact of algorithmic parameters on the overall 
performance and the impact of automatic adaptation of the parameters

- Carry out computational experiments required for the achievement of 
the research goals

- Plan work activities to ensure deliverables and deadlines are met 
while continuously monitoring progress

- Disseminate the results via project meetings, conference papers, 
conference presentations and journals of the highest quality as well as 
impact delivery activities (special session and tutorial organization at 
conferences

- Collaborate closely with research collaborators world-wide

- Undertake activities to increase own leadership and professional 
standing in the community and international scale

- Contribute to the intellectual growth of the research group by 
co-supervising research students



About the University and 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.


Salary

332,550-450,000 RMB per annum for 2 years.

Meal supplement and festival expenses allowances as well as high/low 
temperature subsidies are also provided. Funding is available for 
conference attendance and collaborative research visits to related 
research groups in organizations world-wide. The AI-Theory Lab at 
SUSTech maintains effective collaborations with all the research 
organizations with major expertise in the theory of bio-inspired 
computation world-wide.


Line Manager

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. Further information can be accessed 
via his personal webpage: https://peteroliveto.github.io/>


Key Words

Artificial Intelligence, Bio-Inspired Computation, Theory



Pietro Oliveto
Professor of Computer Science
南方科技大学/工学院/计算机科学与工程系
广东省深圳市南山区学苑大道1088号