PhD in Digital Twins for Electrified Construction

KTH Royal Institute of Technology; Stockholms kommun; On-site; SEK 379,440 - 468,720; Full time

Job summary

KTH Royal Institute of Technology invites applications for a two-year licentiate doctoral position in DISSECT, focusing on data-driven models and decision support for emission-free, resource-efficient construction. The research spans GeoBIM, 3D voxel ground models, material tracking and sensor data analysis, aiming for digital-twin-based electrified groundwork decisions.

The Division of Geoinformatics at KTH leads this effort, with supervision proposed by Gyözö Gidofalvi and Jonas Mårtensson.

Qualifications

• Preferred qualifications include experience with simulation, optimization or digital twin systems.
• Experience with cloud environments and containerized applications is desirable.
• Experience handling large datasets.
• Interest in energy systems and sustainability.
• Experience from research or industry projects.
• Good communication skills in English and Swedish are required in day-to-day work.

Responsibilities

• Contribute to developing data-driven models and decision support for electrified groundwork construction.
• Work with GeoBIM, 3D voxel models, material flows and mass estimation.
• Collaborate on optimization of construction processes and charging constraints.

Skills

Simulation

Optimization

Digital twin

Cloud environments

Containerized apps

Large datasets

English & Swedish communication

Education

Master's degree or equivalent in a relevant field

Tools

Docker

Kubernetes

GeoBIM tools

Geospatial databases

Job description

KTH Royal Institute of Technology invites applications for a two-year licentiate doctoral position in DISSECT, focusing on data-driven models and decision support for emission-free, resource-efficient construction. The research spans GeoBIM, 3D voxel ground models, material tracking and sensor data analysis, aiming for digital-twin-based electrified groundwork decisions.

The Division of Geoinformatics at KTH leads this effort, with supervision proposed by Gyözö Gidofalvi and Jonas Mårtensson.