PhD Candidate: Digital Twins for Electrified Construction

Kungliga Tekniska högskolan; Stockholms kommun; On-site; SEK 424,080 - 513,360; Full time

Job summary

KTH Royal Institute of Technology, School of Architecture and Built Environment, invites applications for a two-year licentiate doctoral position in DISSECT, developing data-driven models and decision support for emission-free, resource-efficient and electrified construction.

The doctoral student will work with material and logistics layers, GeoBIM, and 3D voxel models, focusing on model predictive control and reinforcement learning for digital-twin decision support.

Qualifications

• Master's or equivalent in a relevant field (geoscience/geoinformatics).
• Strong analytical and programming skills.
• Experience with data science, ML, simulation or optimization.
• Strong communication in English and Swedish.

Responsibilities

• Develop data-driven models for emission-free, resource-efficient construction.
• Work with GeoBIM and 3D voxel models for materials and logistics.
• Contribute to digital-twin based decision support for electrified groundwork construction.
• Collaborate within the DISSECT consortium and supervision team.

Skills

Simulation/Optimization

Cloud environments & containers

Large datasets

Energy systems & sustainability

Research/industry projects

English & Swedish communication

Education

Master's degree or equivalent

Job description

KTH Royal Institute of Technology, School of Architecture and Built Environment, invites applications for a two-year licentiate doctoral position in DISSECT, developing data-driven models and decision support for emission-free, resource-efficient and electrified construction.

The doctoral student will work with material and logistics layers, GeoBIM, and 3D voxel models, focusing on model predictive control and reinforcement learning for digital-twin decision support.