职位信息
Doctoral student in Applied Math. within Optimization and Systems Theory
2024年11月21日截止
We focus on developing optimization algorithms, methods, and fundamental theory, and focus on applications in planning, signal processing, AI, and machine learning (ML). You will work in the project ADAPCOS (Autonomous Underwater Vehicle Data Processing, Communication, and Swarm Optimization in Contested and Denied Undersea Environments) which is a collaboration between KTH, Saab, and Purdue University.
We will, for example, work on analyzing and comparing classical optimization-based methods versus AI and ML alternatives. We are particularly interested in analyzing and understanding weaknesses in AI/ML systems and improving their robustness.
A strong interest in mathematical programming (e.g., mixed-integer optimization) is a great advantage.
In the project we will develop algorithms, computational methods, and implement these in Python (or a similar programming language) to test and compare methods.
To be admitted to postgraduate education (Chapter 7, 39 § Swedish Higher Education Ordinance), the applicant must have basic eligibility in accordance with either of the following:
passed a second cycle degree (for example a master's degree), or
completed course requirements of at least 240 higher education credits, of which at least 60 second-cycle higher education credits, or
acquired, in some other way within or outside the country, substantially equivalent knowledge
In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates will be assessed upon their ability to:
independently pursue his or her work
collaborate with others,
have a professional approach and
analyse and work with complex issues.
https://www.kth.se/lediga-jobb/767669?l=en
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@留德华叫兽：系美国Clemson大学数学硕士(运筹学方向)、Ph.D. candidate，欧盟玛丽居里学者，德国海德堡大学数学博士(离散优化、图像处理)，读博期间前往意大利博洛尼亚大学、IBM实习半年，巴黎综合理工访问一季。现任德国无人驾驶资深研发工程师。
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