Open position at Artificial Intelligence Center FEE CTU
Ph.D. in Mathematical Optimization and Control (Fairness in AI)
- Work schedule
- Karlovo nám. 293, 120 00 Praha-Nové Město, Česko
Are you seeking an excellent doctoral program where you can apply your mathematical skills to develop fair and transparent AI algorithms? Look no more! Join our center as a full-time Ph.D. student to work on a prominent Horizon Europe project and kickstart your research career.
AutoFair project for human-compatible AI
As a Ph.D. student, you will join the AutoFair project which we at CTU coordinate. This extensive project was supported by the Europen Commission and its mission is to address the matter of transparency and explainability of AI using approaches inspired by control theory. It is a part of an EC initiative toward ensuring AI development that is trustworthy and transparent.
In order to deliver AI systems with full consideration of social welfare, we are developing training algorithms that incorporate appropriate measures of aspects of social concern. Our goal is to develop training optimization algorithms with theoretical guarantees of solution quality, which also work well in practice.
Jakub Mareček, Ph.D. has worked in two start-ups, IBM Research Ireland, and at the University of California LA, the University of Edinburgh, and the University of Toronto. As the Head of the Optimization group in the AI Center, he designs and analyses algorithms for optimization and control problems across a range of application domains, including power systems, quantum computing, and robust statistics.
You will benefit from close collaboration with other members of the AutoFair project, namely the teams of Shie Mannor (Technion), Robert Shorten (Imperial), Dimitris Gunopulos (NKUA), and Ioannis Emiris (Athena RC).
Optimization research in the AI Center
Research on the intersection of mathematics, computer science, and electrical engineering with a clear mission: find the optimal solution using advanced computational methods.
In our basic research, we focus on study extensions towards certain smooth, non-convex feasible sets and objective functions and time-varying feasible sets and objective functions.
The smooth non-convex problems, known as commutative and non-commutative polynomial optimization, have extensive applications in power systems, control theory, and machine learning, among others.
Salary and benefits
The position is full-time and limited to 3 years, but can be extended in case of mutual interest.
The studentship comes with a monthly salary adjusted to approximately match the average salary in Prague, the Czech Republic (which currently stands at approximately EUR 23 000 p.a. before a notably low tax).
You are entitled to 6 weeks of paid vacation which you will find useful when exploring the beautiful parts of our country including a number of UNESCO landmarks.
Get excited about a travel budget for attractive conferences abroad, regular internal seminars, an unlimited supply of coffee (very appreciated).
Our labs are located on the university campus in the historical city center with a view of Prague Castle, so perfect transport accessibility is another obvious advantage.
The Czech capital regularly ranks among the five best Eropean cities to live in.
What we appreciate the most about our research center is its inspirational and supportive environment. We love to cooperate across teams and benefit from our diverse research network.
It‘s interesting that there are professors known all over the world and yet they don‘t give you the feeling they are something more. They come to your presentation, take interest in your problem at the seminar and try to help you.
Master's degree in Computer Science, Mathematics, Operations Research, or related disciplines.
Excellent mathematical aptitude, as demonstrated by involvement in mathematical olympiads, relevant coursework, or undergraduate research.
A preference is given to:
candidates with experience with non-trivial analysis of (optimization) algorithms,
candidates with experience in programming in Python,
candidates with experience with Deep Learning.
How to apply
- Send your structured CV and· motivation letter to our HR Manager firstname.lastname@example.org or via the form below.
- We will contact you in approx. two weeks whether you qualify for the position and if we think you would be a good fit for our team.
- You will then get an interview with our Optimization researchers.
- If you agree, we will invite you for a visit to give a talk at our internal seminar. You will meet our team, spend a day with us in meetings, have lunch and we will show you around.
- Shortly after, you will get a final answer and we will decide on a suitable starting date.
Zakládáme si na inkluzivite a diverzite. Chceme mít lidi po hromadě lidi, kteří jsou skvělí v inkrementálním výzkumu Opakem jsou moonshoty - exponenciální výzkum - namyslíte, kde může být daný problém za 10 let. Pro špičkové výsledky se snažíme kombinovat oba přístupy.