Internship in Data Annotation and Training for Deep Learning

Eurac Research; Bolzano; On-site; EUR 6,700 - 12,000; Full time

Benefits offered by this job

International research environment

Professional development and training

Outdoor lifestyle in a cyclable city

Job summary

The Institute for Renewable Energy in Bolzano invites applications for an internship in the Energy Efficient Buildings group. The role focuses on computer vision and deep learning to promote energy efficiency in buildings.

Duration is 4 to 6 months, with tasks including image annotation, field data collection in Bolzano, tool enhancement, and model training support. English fluency required; Italian or German is a plus. The environment is international and interdisciplinary.

Qualifications

• Bachelor’s or Master’s degree in architecture, urban planning, engineering, or computer science preferred.
• Experience with CAD or BIM is preferred but not required.
• Fluency in spoken and written English. Italian and/or German is a bonus.

Responsibilities

• Annotate images used to train deep learning models for façade parsing.
• Collect 360-degree images for a pilot study in Bolzano – by foot or by bicycle.
• Support the development and enhancement of the in-house image annotation tool.
• Support the training and deployment of deep learning models for façade parsing.

Skills

Image annotation

Education

Architecture/Engineering/CS degree

Tools

CAD/BIM

Job description

Institute for Renewable Energy

Short description of the position:

Are you passionate about the decarbonisation of buildings? Are you curious about how computer vision and deep learning can be used to analyse and promote energy efficiency in buildings? If so, you could be a great fit as an intern with the Energy Efficient Buildings group at Eurac Research!

The duration of the internship is at least 4 months and up to 6 months (to be agreed upon with the candidate).

Tasks:

• Annotate images used to train deep learning models for façade parsing.
• Collect 360-degree images for a pilot study in Bolzano – by foot or by bicycle.
• Support the development and enhancement of the in-house image annotation tool.
• Support the training and deployment of deep learning models for façade parsing

Requirements:

• Bachelor’s or Master’s degree in architecture, urban planning, engineering, or computer science preferred. Candidates with other educational backgrounds with a strong interest may also apply.
• Experience with CAD or BIM is preferred but not required.
• Fluency in spoken and written English. Italian and/or German is a bonus.
• Experience working in a research setting is a bonus.

We offer:

• A supportive, international, and interdisciplinary research environment.
• Access to professional development and training opportunities.
• An attractive workplace in a highly cyclable city offering excellent access to outdoor and mountain activities.