Program Description

About BIMSA and the Group

The Beijing Institute of Mathematical Sciences and Applications (BIMSA), established in 2020, is a world-class mathematics research institution co-sponsored by the Beijing Municipal Government and Tsinghua University. It is led by the world-renowned mathematician Prof. Shing-Tung Yau.

We are establishing a new research group dedicated to advanced intelligence optimization theory, algorithm design, and their broad industrial applications. The group’s mission is to push the frontiers of optimization science, covering both the theoretical foundations and high-performance computational implementations, and to deploy these innovations in fields such as artificial intelligence, quantitative finance, supply chain resilience, and embodied intelligence.

The core pillar of the group’s work is Yau’s Affine-Normal Descent (YAND), a novel geometric optimization paradigm pioneered by Prof. Shing-Tung Yau. The immediate flagship application is YAND-MVSK, an industrial software platform for higher‑moment portfolio optimization developed in strategic collaboration with leading quantitative investment firms. Beyond YAND, the group actively investigates a broad spectrum of state-of-the-art optimization methodologies, including large-scale convex and non-convex programming, stochastic optimization, semidefinite programming, and learning-based optimization, with a strong emphasis on both theoretical breakthroughs and robust, deployable software.

We seek outstanding researchers and engineers in optimization theory, high‑performance scientific computing, and artificial intelligence to join this fast‑moving, high‑impact initiative.

Open Positions

We are recruiting for multiple positions, including Assistant Professor (tenure-track), Postdoctoral Fellow, and Research Engineer (non-tenure-track). Exceptionally qualified senior candidates may be considered for tenured Associate Professor or higher-level positions. The requirements are as follows:

1. Research Directions

Candidates should have a solid background in one of the following research areas:

·        Optimization Theory and Algorithms: geometric optimization, convex and non-convex optimization, large-scale optimization, polynomial optimization, stochastic optimization, semidefinite programming, non-smooth optimization, and related fields.

·        High-Performance Scientific Computing: parallel computing (MPI, OpenMP, CUDA), numerical linear algebra, sparse matrix computation, and low-latency system design.

·        Machine Learning and AI Theory/Algorithm Design: optimization theory and algorithm design for deep learning, learning to optimize, large models, AI Agents, and automatic differentiation.

2. Qualifications

Assistant Professor

• A Ph.D. in applied mathematics, operations research, computational mathematics, computer science, or a related field.
• Outstanding research achievements in optimization, artificial intelligence, or scientific computing.
• Independent research capabilities and a spirit of interdisciplinary collaboration.
• Experience in developing industrial-level optimization solvers and high-performance computing software is preferred.

Postdoctoral Fellow

• A Ph.D. (or near completion) in operations research, computational mathematics, computer science, or a related field.
• Research experience in optimization, numerical linear algebra, high-performance scientific computing, or machine learning.
• Proficiency in MATLAB or Python, with familiarity in C++ programming.
• Experience in developing industrial-level optimization solvers and high-performance computing software is preferred.

Research Engineer

• A Ph.D. in engineering mathematics, applied mathematics, computer science, computational mathematics, operations research, or a related field.
• Excellent programming skills, with proficiency in C++, MATLAB, or Python.
• Hands-on experience with parallel computing (MPI, OpenMP, CUDA) and numerical libraries (Eigen, BLAS, LAPACK, Intel MKL) is preferred.
• Experience in AI Agent development is preferred.
• Experience in building high-performance optimization solvers or low-latency financial systems is preferred.

3. Core Responsibilities

Assistant Professor

• Participate in the development of theory and algorithms for YAND-related projects, and engage in research on high-performance computing and machine learning.
• Publish high-quality research results.
• Mentor students and contribute to the long-term development of the team.
• Other tasks assigned by the team lead.

Postdoctoral Fellow

• Participate in research on YAND optimization algorithms and related theory, and develop MATLAB/Python codes.
• Participate in the development of the industrial-level C++ core library for YAND-related projects solvers.
• Publish high-quality research results.
• Other tasks assigned by the team lead.

Research Engineer

• Drive the implementation of YAND algorithms in various industrial scenarios.
• Design and implement industrial-level high-performance optimization solvers for YAND-related projects using C++.
• Develop parallel computing modules, application programming interfaces, and AI Agent modules.
• Participate in software testing and documentation.
• Other tasks assigned by the team lead.

4. Compensation and Benefits

• Competitive annual salary, commensurate with qualifications and experience. For candidates with extensive experience in industrial-level optimization solvers or high-performance computing, the salary may be adjusted upward.
• Benefits: talent apartments offered at below-market rates; annual health check-ups; shuttle bus service (BIMSA/Tsinghua); assistance with children’s school enrollment in the BIMSA district.
• Research support: generous start-up funding, ample travel grants for academic communication, and access to top-tier computational resources.
• Unique opportunity: conduct academic research and engineering implementation under the direction of Prof. Shing-Tung Yau, and collaborate with leading industry partners; work on the beautiful campuses of BIMSA and Tsinghua University; excellent career prospects in academia, quantitative finance, or broader industry.

Review of applications will begin immediately and continue until all positions are filled.