Special Recommendation: Cross‑Disciplinary Innovations in the Intelligent Complex Systems Lab

Special Recommendation | Complex Intelligent Cross‑Innovation in the Laboratory of Fundamental Theory and Key Technologies for Intelligent Complex Systems

Due to the implementation needs of major national scientific tasks, the Complex Intelligent Cross-disciplinary Innovation Team of the Laboratory of Fundamental Theory and Key Technologies for Intelligent Complex Systems at Fudan University is openly recruiting several full-time researchers, postdoctoral fellows, and engineers. We welcome outstanding talents with relevant research backgrounds and development potential to join us.

1. Job Openings

Full-time positions for major innovation projects and full-time postdoctoral researchers (4-6), and development engineers (2-4).

2. Academic Fields

Targeting research areas such as complex networks and systems science, intelligent science and technology, control science and engineering, system simulation and systems engineering, brain and cognitive science, artificial intelligence, brain‑inspired intelligence, computational neuroscience, data science, or statistical modeling.

III. Directions and Qualification Requirements for Full‑time Researchers and Postdoctoral Positions in Major Innovation Projects

Direction 1: Complex Agent Theory and Computation

Job Responsibilities: Conduct research on complex agent design and computation, complex multi-agent systems, and related theories and methods.

Qualifications:

– Holds or will soon hold a Ph.D. in Computer Science, Automation, Applied Mathematics, Statistical Physics, Electronic Science and Technology, Computational Neuroscience, or related fields;

– Has a research background in multi-agent systems, brain-inspired neural computation, digital brain, or related areas;

– Familiar with common machine‑learning frameworks and toolchains, proficient in PyTorch, and knowledgeable about TensorFlow, scikit‑learn, XGBoost/LightGBM, etc.; strong research‑oriented programming skills;

– Preference given to candidates with high‑impact papers, open‑source projects, or related research achievements.

Direction 2: Training and Inference of Complex Intelligent Agents

Job responsibilities: Conduct research on training, inference, and learning mechanisms for various AI agents and brain‑inspired agents, as well as task optimization, alignment, and efficient inference for large models and multi‑agent systems.

Qualifications:

– Holds or will soon hold a Ph.D. in computer science, automation, applied mathematics, statistical physics, electronic science and technology, computational neuroscience, or related fields;

– Familiar with large model or multimodal model training pipelines, with a research foundation in areas such as large model alignment, supervised fine‑tuning, reinforcement learning, model compression, or inference acceleration;

– Proficient with common machine‑learning frameworks and toolchains, skilled in PyTorch, and knowledgeable about TensorFlow, scikit‑learn, XGBoost/LightGBM, etc.; strong research‑oriented programming ability;

– Preference given to candidates with high‑level papers, open‑source projects, or related research achievements.

Area 3: Digital Twin Scenario Modeling and Simulation

Job Responsibilities: Conduct research on digital‑twin scenario modeling and simulation, including theory and methods for complex scenario modeling, dynamic simulation, state perception, and simulation analysis.

Qualifications:

– Holds or will obtain a Ph.D. in computer science, automation, system simulation, artificial intelligence, or related fields;

– Has a research foundation in digital twins, system modeling and simulation, or related areas;

– Possesses strong independent research and programming abilities; candidates with high‑level papers, open‑source projects, or related research achievements are preferred.

Direction 4: Complex Intelligent Theory and Cross‑Disciplinary Technologies

Job Responsibilities: Conduct interdisciplinary research on complex systems, network science, and intelligent science theory, focusing on frontier topics such as machine social intelligence, intelligent swarm systems, and human‑machine hybrid intelligent systems.

Qualifications:

– Holds or will obtain a Ph.D. in systems science, computer science, automation, applied mathematics, statistical physics, robotics, artificial intelligence, or related fields;

– Has a research foundation in frontier areas such as network science, embodied intelligence, unmanned systems, human‑computer interaction, and brain‑machine interfaces;

– Demonstrates strong independent research and programming abilities; candidates with high‑impact papers, open‑source projects, or related research achievements are preferred.

4. Engineer Position Directions and Job Requirements

Job Focus: Development of Complex Agent Simulation Platform

Job Responsibilities:

– Responsible for architecture design, system development, and feature implementation of the complex agent simulation platform;

– Participate in the development, optimization, deployment, and maintenance of the simulation engine, algorithm modules, experimental workflows, and related platform components;

– Support the implementation of research projects within the team, driving platform construction and practical application;

– Collaborate with researchers to conduct technology development and system validation.

Job Requirements:

– Holds or will soon obtain a master’s degree or higher (exceptionally outstanding undergraduate graduates are also welcome), in computer science, software engineering, automation, electronic information, or related fields;

– Strong ability in system development and engineering implementation, familiar with at least one programming language such as Java, Python, or C++;

– Familiar with Kubernetes platform architecture and application deployment, and with common engineering development tools;

– Experience in simulation platforms (front‑end/back‑end), multi‑agent systems, or distributed systems is a plus;

– Possesses strong teamwork skills and the ability to solve problems independently.

V. Compensation and Benefits

– The salary structure and performance evaluation for each position follow Fudan University’s relevant compensation regulations; exceptionally outstanding applicants may negotiate terms. Actively support the application for various national and Shanghai municipal research projects and talent funds.

– The Complex Intelligent Cross‑Disciplinary Innovation Team, led by Professor Li Xiang (National Distinguished Young Scholar, leader of ten‑thousand‑talent program), includes numerous interdisciplinary mid‑career and young scientists, post‑doctoral researchers, research assistants, and a group of master’s and doctoral students, offering comprehensive support for academic and career development.

– We provide an excellent office environment and world‑class research platforms, assist with housing issues (e.g., post‑doc apartments), and offer opportunities for exchanges and visits to top international universities and research institutions.

– Outstanding post‑doctoral researchers may be given priority recommendation to stay at Fudan University, and those with outstanding performance as full‑time researchers can be promoted within this series or transferred to permanent‑track positions.

– Full‑time researchers involved in major innovative projects can apply for university‑provided temporary faculty apartments; those applying for Shanghai household registration will be processed according to relevant Shanghai policies.

– In accordance with Fudan University policies, we assist children in applying for admission to Fudan University affiliated kindergarten and primary school, enjoying the same benefits as other faculty and staff.

6. Application Method

Scan the QR code below, fill out the form, then add the staff member on WeChat to submit your personal materials.

Application Materials:

Subject: “Major Innovation Task Full‑time Researcher, Postdoc (or Engineer) Application + Name”

– Curriculum Vitae (including education background, research experience, representative achievements such as 3‑5 key papers or GitHub open‑source links, awards, research interests, etc.);

– Research Statement (summary of previous research results, future research plan for the major innovation task full‑time researcher or postdoc, referee information, etc.).

This recruitment is open-ended, and the research group will screen resumes preferentially; candidates who pass the initial review will be scheduled for interviews promptly.Members of the Jizhi Book Club are given priority consideration; we welcome talented young professionals in related fields from the community to apply!!

Laboratory Introduction

The Laboratory of Fundamental Theory and Key Technologies for Intelligent Complex Systems at Fudan University was officially established in June 2018 and is a second‑level internal research institution operating under Fudan University. Leveraging the interdisciplinary strengths of Fudan’s five major disciplines—social sciences, humanities, natural sciences, medicine, and engineering—and building on the university’s strong tradition of cross‑disciplinary research and development, the lab focuses on “integrated next‑generation intelligent computing, cyberspace, and physical environment multi‑dimensional intelligent complex systems,” emphasizing the development of novel algorithms, seamless integration of efficient virtual computing spaces and physical environments, and autonomous dynamic evolution. It provides core algorithms and technological guarantees for the integration, intelligent adaptation, and scalable deployment of existing intelligent complex systems.

The lab currently includes 2 recipients of national-level important talent programs, 3 recipients of national-level youth talent programs, 5 recipients of Shanghai’s important talent program, 1 Eastern Scholar, and a group of interdisciplinary young researchers and engineering technicians. It undertakes numerous national key R&D projects, major projects of the Natural Science Foundation, Shanghai municipal science and technology commission’s key projects in social development, fundamental theory, and high‑tech, sub‑projects of major municipal special initiatives, as well as large‑scale health insurance budgeting and modeling projects in Shanghai and other major cities.

On September 14, 2023, the Ministry of Education officially approved the doctoral degree authorization point for the first-level discipline “Complex Systems Science and Engineering.” This degree program is based on Fudan University’s Laboratory of Fundamental Theory and Key Technologies for Intelligent Complex Systems (department code 089) and will carry out graduate admissions. The professional code for “Complex Systems Science and Engineering” is 079901, with three enrollment directions: 01 Complex Systems Theory (including applied mathematics), 02 Complex Systems Modeling and Control (including biomedical engineering), 03 Complex Systems Science and Engineering.

Main objectives of the laboratory:

1. Emphasize both fundamentals and applications, integrate intelligence with industrialization, and combine civilian and defense needs to study common issues of intelligent complex systems, exploring efficient and scientific modeling theories, methods, and tools for intelligent complex systems.

2. Develop intelligent modeling methods, model prototype sets, software, and verification environments for various typical application domains of complex systems that are crucial to the national economy, people’s livelihood, and national security, aiming to enhance the modernization of governance systems and capabilities, ultimately achieving multidimensional digital twins.

3. For disciplines such as systems science, next‑generation artificial intelligence, public and emergency management, build a comprehensive frontier interdisciplinary talent cultivation and scientific research innovation system.