Description: 

As part of our research in the Robot Lab, we work with a large variety of (waste) wood. Part of our research addresses how to process wood harvested from demolition – with the intent of re-using it in the future. For this, we are developing a process, and the systems and machinery to measure and analyze the properties of beams and planks – a process we call Wood Intake. This process creates different kinds of data, which we analyze to determine whether wood is useful for specific purposes.

To visualize this process for current and future users, we are continuing the development of an existing front-end dashboard application as a web-based platform. The current dashboard already visualizes the Wood Intake process by displaying live 3D and 2D scan data of wood elements captured by the Wood Intake machine, together with processed analysis results and material information.

The continuation of this internship will focus on extending the platform by integrating business and production-related data into the existing visualization environment. This includes connecting the scanned wood data with Digital Twin software, process planning information, robotic operations, and predictive analytics related to throughput, production time, material yield, environmental impact, and estimated manufacturing costs.

The front-end application will most likely consist of: 
React/Vue or Next.js (front-end), 
Python (back-end integrations, analytics, or middleware tools), 
Three.js framework (for 3D data visualization in the front-end), 
SQL/redis (persistent process dataflow management), 
Docker (deployment and containerization). 

You will work with the existing APIs and infrastructure developed at the Robot Lab to access, process, and visualize wood intake and production-related data stored in our server-based database systems. This involves using HTTP protocols for communication with database and analysis APIs, as well as MQTT protocols for event-driven updates and live process synchronization between systems.

The front-end application should also include analytics and KPI sections for every process and wood entry, enabling the generation of reports on material impact, potential yield, production feasibility, and manufacturing performance of scanned reclaimed wood resources within the EUWoodCircles project.

Deliverables:

Front-end application that can visualize data & analysis and integrate with the Digital Twin software.

Required knowledge and skills

• Familiarity with (any parts) of the tech stack outlined in the description is a big plus
• Good knowledge of Python / JavaScript

Deadline for application:

June 20th 2026