Jobs at Aalto University

Conduct doctoral research on power system dynamics, focusing on grid-generator interactions, subsynchronous resonance, torsional oscillations, and converter-driven oscillations. Analyze PMU data, develop monitoring and signal-processing methods, build and validate dynamic simulation models, evaluate resonance risks, and assess mitigation strategies. Collaborate with academic researchers and industry partners including TVO and Fingrid.

Conduct research in trustworthy machine learning, focusing on model and pipeline provenance, integrity, adversarial robustness, privacy, fairness, AI/MLBOM, and proof-carrying machine learning. Publish research, present findings, collaborate internationally, and contribute to teaching. Candidates need strong Python and PyTorch skills, applied mathematics expertise, shared-codebase experience, and a completed Master's degree before the contract begins.

Conduct research in quantum algorithms and quantum information, developing hybrid quantum-classical methods for computational problems in bioinformatics, plant breeding, biomaterial synthesis, and enzyme design. Evaluate and benchmark quantum models against classical baselines, publish high-impact research, collaborate across disciplines, supervise PhD students, and contribute to teaching.

Develop fundamental theory and practical algorithms for continual reinforcement learning in non-ergodic, changing real-world systems. Responsibilities include trajectory-centric optimization, change detection, adaptive policies with safety guarantees, integration into state-of-the-art reinforcement learning algorithms, and validation through simulations and robot hardware experiments. Researchers will work collaboratively within Aalto University’s Cyber-physical Systems Group and pursue doctoral studies in electrical engineering.

Build hardware-aware AI behavioral models for analog and RF circuits using Python, validate them against simulations and measurements, and perform hardware-algorithm co-design for energy-efficient 6G transmitters. The role includes publishing research, completing a doctoral thesis, teaching, and collaborating internationally. Candidates need a relevant Master's degree, Python-based machine learning experience with PyTorch or similar tools, and strong backgrounds in signals, systems, and analog circuit theory.

Conduct experimental research on hybrid magnonics-photonics platforms coupling superconducting qubits, magnons, spin ions, microwave systems, and optical cavities. Work may involve nanofabrication, thin-film growth, cryogenic measurements, spectroscopy, optical fibre imaging, and quantum transduction. Doctoral researchers pursue PhDs, while postdoctoral researchers lead research topics and support doctoral team members. Researchers are expected to publish high-impact results and communicate findings internationally.

Conduct research on photomemristor arrays for biological neuron interfaces and bio-machine hybrid systems. Design and fabricate devices with suitable photoresponsivity, wavelength response, and biocompatibility; investigate materials and device structures; and integrate selected devices into closed-loop systems processing neuronal signals. Work includes thin-film growth, nanofabrication, electronic and optoelectronic characterization, publication, and research communication.

Conduct experimental research on nanoparticle-embedded OLEDs to control emission properties such as polarization, color, and angular distribution. Design, fabricate, and characterize nanoparticle arrays and OLED devices using nanofabrication, optical instrumentation, and electronics. Collaborate with theorists on simulations and device optimization, disseminate scientific results, and contribute to commercialization efforts. The position is based at Aalto University’s Otaniemi campus and includes a two-year initial contract.

Conduct research on the international political economy of digital infrastructures and complete a Master's thesis within the Digital Economic Security Lab. Projects may involve survey analysis, cloud adoption, machine learning, econometrics, Internet measurement, sanctions, digital infrastructure, and supply chain research. Assistants will analyze datasets, develop research methods, write academic material in English, and collaborate with interdisciplinary lab members under faculty supervision.

Integrate, deploy, diagnose, and safely test robotic systems using platforms, sensors, computing systems, and safety functions. Configure ROS/ROS2 environments, develop HIL/SIL test benches, conduct field tests, collect data, and document results. Support electronics and embedded-systems prototyping, maintain shared laboratory equipment, prepare user instructions, and promote laboratory, electrical, and robotic safety. The role supports researchers and students within Aalto University's MIDAS research infrastructure.

Conduct doctoral research on backscatter-assisted wireless positioning for non-line-of-sight environments. Develop signal models, algorithms, and estimation methods; design software-defined radio prototypes; run simulations and experiments; analyze measurement data; publish findings; complete doctoral studies; and participate in limited teaching and academic activities.

Conduct independent, high-quality research in sustainable business within Aalto University’s Organizations and Management discipline. Publish in leading international journals, develop a personal research agenda, teach one course annually, supervise master’s theses, and potentially contribute to PhD supervision. Candidates should have recently completed or be completing a relevant PhD, demonstrate teaching and international publication capabilities, and work fluently in English. The position is full-time, in-residence, and fixed-term for two years.

Conduct computational astrophysics research on stellar dynamos, magnetic activity, habitable exoplanets, and space weather. Develop GPU-accelerated global and local MHD simulations, calibrate models against observations, prepare datasets for machine learning, couple dynamo models with stellar corona and wind models, analyze large-scale simulations, publish findings, release research data and code, and contribute to departmental teaching.

Develop biology-informed probabilistic machine learning methods for dynamical systems as part of a PhD thesis. The work will combine mechanistic ordinary differential equation models with Gaussian processes, Bayesian inference, uncertainty quantification, heterogeneous biological trajectories, partial observability, and interpretable mechanistic discovery. The researcher will work across computational systems biology and artificial intelligence research groups, with opportunities to explore foundation models and biomedical applications.