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Kristina Vassiljeva

5 months ago

PhD Position in Hybrid Modelling of Thermal Grids Tallinn University of Technology in Estonia

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

Estonia

University

Tallinn University of Technology

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Keywords

Computer Science
Environmental Science
Mechanical Engineering
Mathematics
Fluid Mechanics
Python Programming
Digital Twin Technology
Dynamical Systems
Data-driven Modeling
District Heating
Control System
Physics
Applied Mathematic
energy storage systems

About this position

This PhD position at Tallinn University of Technology focuses on the development of hybrid modelling approaches for thermal grids, specifically district heating and cooling systems. The research aims to integrate physics-based models with data-driven techniques to enhance the performance, reliability, and efficiency of thermal energy infrastructures. By combining interpretability from traditional physics-based models with the adaptability of machine learning, the project seeks to address challenges in model calibration, predictive performance, and computational efficiency.

The successful candidate will work on control-oriented models that represent the dynamic behaviour of energy systems, leveraging operational data to improve model calibration and validation. The research will contribute to the creation of digital twin frameworks for district heating systems, supporting advanced monitoring, optimisation, and operation. Key challenges include integrating physics-based models with operational datasets, developing scalable hybrid modelling approaches, and validating models through real-world case studies.

Supervision will be provided by Associate Professor Kristina Vassiljeva (School of Information Technologies, Department of Computer Systems, Centre for Intelligent Systems) and Full Professor Anna Volkova (School of Engineering, Department of Energy Technology, Smart District Heating Systems and Integrated Assessment Analysis of Greenhouse Gases Emissions). The project is embedded within TalTech’s multidisciplinary and internationally collaborative research environment, which is renowned for its strengths in digitalisation and sustainable energy systems.

Applicants should possess a strong background in applied mathematics, control theory, or machine learning, with experience in data-driven modelling and time-series analysis. Familiarity with dynamical systems theory, numerical optimization, and programming skills in Python or MATLAB are required. The position offers the opportunity to contribute to the digitalisation and decarbonisation of thermal energy systems, with expected outcomes including improved monitoring, optimisation, and operation of district heating infrastructures.

Applications are open from 01.06.2026 to 30.06.2026. For further details and to apply, visit the provided application link. The university offers a modern research environment and strong international collaboration, supporting doctoral research across multiple disciplines.

Funding details

Available

What's required

Applicants should have a strong background in applied mathematics, control theory, or machine learning. Experience in data-driven modelling, especially with time-series data, is desirable. Familiarity with dynamical systems theory and numerical optimization is expected. Programming skills in Python or MATLAB for handling large datasets are required. No specific GPA or language test requirements are mentioned.

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Professors

Associate Professor at Tallinn University of Technology

University Name
Country flag

Estonia

Research Interests

Power System

Control System

Demand-side Management

Energy Consumption

Energy Modelling

Full Professor at Tallinn University of Technology

University Name
Country flag

Estonia

Research Interests

Energy Engineering

Environmental Sustainability

District Heating

Mechanical Engineering

Environmental Science