Summer jobs at the Systems Analysis Laboratory

The Systems Analysis Laboratory is hiring interns for the summer of 2023. Summer jobs usually last from the start of June until the end of August, but other arrangements are also possible. Some of the topics are also suitable for first or second-year students. There are also opportunities for summer interns to keep working after the summer on a part-time basis as research and/or teaching assistants.

Interns typically produce a bachelor’s thesis or a special assignment related to their research work. Students doing their bachelor’s theses will prepare a working plan with their advisor for the seminar gathering in June. Many of the topics offer a possibility to continue research work to the master’s thesis phase.

In your application, please specify the topics (17 though 23) that you are interested in. You can also provide an order of preference for the topics you are interested in.

Applications for summer internships are submitted electronically. The deadline for applications is 25 January 2023. Instructions will be available on 10 January at https://math.aalto.fi/en/current/.

For more information on a specific topic, contact the topic's contact person. General questions should be directed to Prof. Nuutti Hyvönen (firstname.lastname@aalto.fi).

We are looking for:

17. One or more students to work on the development and implementation of decision models for risk management. Potential application areas include adversarial risk analysis for safety and security as well as scenario analysis of safety-critical systems. Knowledge of the basics of optimization theory, risk analysis and/or investment science will be helpful. For details, contact Professor Ahti Salo, MSc Joaquin de la Barra and MSc Leevi Olander.    
    
    
18. Several students to work on 1) the development of a spatial decision analysis model for controlling air surveillance systems (also Master’s thesis topic available), 2) the development of a decision analysis model based on measures of team performance in air combat for comparing air combat tactics (also Master’s thesis topic available), 3) the development of a simulation tool for readiness, reach and force fulfillment of aircraft, and 4) the development of plug-ins to the modern air combat environment (MACE) simulation https://www.bssim.com/mace/ . Familiarity with MATLAB and basic statistical analysis are required in all topics. Basic knowledge of decision analysis and optimization are required in Topics 1 and 2. Basic knowledge of simulation and good programming skills are required in Topics 3 and 4. Moreover, experience with C, C++ or C# is required in Topic 4. For details, contact Professor Kai Virtanen.
    
    
19. A student to work on optimisation-based representations of machine learning (ML) models. Applications include adversarial training of ML models, ML-based surrogates for simulation systems, and data-driven optimisation in the field of energy systems. Familiarity with machine learning (tree-based models and neural networks), linear/integer programming and experience with Julia language and GitHub are required. Please contact Professor Fabricio Oliveira for further information.
    
    
20. A student to work on Markov Decision Process based optimization models for maintenance scheduling. We aim to develop condition-based maintenance schedules for systems having multiple dependent components. The position requires familiarity with MATLAB. In addition, basic knowledge of stochastic processes and simulations are useful. For details, contact M.Sc. (Tech.) Jussi Leppinen or Professor Ahti Salo.
    
    
21. A student to work on integrated routing in multi-modal transport systems. The project consists of developing and implementing routing models that encompass two or more transportation modes and allow for optimizing the transport systems simultaneously. Familiarity with linear/integer optimization, an object-oriented programming language and Git/Gitlab are required. A basic knowledge of shell commands is of advantage. Please contact Assistant Professor Philine Schiewe for more information.
    
    
22. A student to work on Efficient Computational Methods for Bi-Level Transmission-Planning Models. We aim to develop suitable solution methods for tackling mixed-integer linear programming (MILP) and mixed-integer quadratically constrained quadratic programming (MIQCQP) problem instances necessary to inform transmission planning in the Nordic power sector. Familiarity with decomposition as well as branch-and-bound methods in optimisation, programming skills in GAMS or MATLAB, and an interest in energy/environmental issues are required. Please contact Afzal Siddiqui for details.
    
    
23. Your own topic proposal related to the laboratory's research or teaching. If you have a suggestion, be in contact with the laboratory's professors (Risto Lahdelma, Fabricio Oliveira, Philine Schiewe, Ahti Salo, Kai Virtanen) prior to submitting your application.

Visit https://math.aalto.fi/en/current/summer_trainees/ for our department's other research groups' topics.