Master Thesis "Material Aware Inline 3D Imaging"

AIT Austrian Institute of Technology GmbH

Master Thesis "Material Aware Inline 3D Imaging"

In cooperation with TU Wien - Institute for Photogrammetry and Remote Sensing

AIT Austrian Institute of Technology is Austria's largest research and technology organisation for applied research. The Center for Vision, Automation & Control located in Vienna invites applications for a master's thesis position.

For this master's thesis project, you will join the Competence Unit High-Performance Vision Systems (HVS), which has over 20 years of research experience in industrial inspection and quality assurance.

The objective of this master's thesis project is to evaluate the potential of material aware 3D reconstruction methods for industrial fast inline inspection applications. Industrial processes often require deeper object knowledge beyond geometrical dimensions, including color, roughness, reflectance behavior and other optically detectable material properties.

The thesis will be carried out in cooperation with TU Wien - Research Group Photogrammetry. The specific focus will be adapted depending on the student's skills and interests, for example towards material-aware Gaussian Splatting representation or multispectral imaging.

Your Tasks

Acquire basic skills in inline optical 3D imaging for process control and automation.
Carry out a literature search and review on state-of-the-art optical detection and reconstruction of material properties.
Explore the potential of material aware Gaussian Splatting and related approaches or sensing methods like multispectral imaging for fast inline quality control.
Use the machine vision lab and a digital-twin Blender model of the lab setup to carry out experiments and collect datasets.
Depending on the thesis direction, expand the existing lab setup with multispectral sensing capabilities.

Your Qualifications

Ongoing master's studies at TU Wien in Geodesy and Geoinformation, Computer Vision/Image Processing, Computer Science, Physics, Mathematics or similar.
Good knowledge in computer vision and/or image processing.
Interest in machine vision, computer graphics and machine learning.
Experience in at least one programming language such as Python or C++; CUDA, OpenCV or Blender experience is advantageous.
Hands-on lab work experience with image acquisition using industrial or digital imaging is advantageous.
Experience in material aware object representation such as Ref-Gaussian or Material-Informed GS is advantageous.
High level of commitment and team spirit.
Very good English skills, spoken and written.

What To Expect

Duration of the master's thesis project: 6 months.
Start date: ideally June 2026, with flexibility depending on availability.
EUR 1.027,40 gross per month for 20 hours per week based on the collective agreement, plus additional company benefits.
Opportunity to work on a real-world research challenge from collaborations with industrial partners.
Hands-on experience with cutting-edge imaging technologies and mentoring from AIT and TU Wien.

Please submit your application documents including CV, cover letter, relevant certificates, transcript of records and proof of identity online.

Apply now

Bewerben

.js-only-skeleton { display: none !important; }

Master Thesis "Material Aware Inline 3D Imaging"

In cooperation with TU Wien - Institute for Photogrammetry and Remote Sensing

Your Tasks

Acquire basic skills in inline optical 3D imaging for process control and automation.
Carry out a literature search and review on state-of-the-art optical detection and reconstruction of material properties.
Explore the potential of material aware Gaussian Splatting and related approaches or sensing methods like multispectral imaging for fast inline quality control.
Use the machine vision lab and a digital-twin Blender model of the lab setup to carry out experiments and collect datasets.
Depending on the thesis direction, expand the existing lab setup with multispectral sensing capabilities.

Your Qualifications

Ongoing master's studies at TU Wien in Geodesy and Geoinformation, Computer Vision/Image Processing, Computer Science, Physics, Mathematics or similar.
Good knowledge in computer vision and/or image processing.
Interest in machine vision, computer graphics and machine learning.
Experience in at least one programming language such as Python or C++; CUDA, OpenCV or Blender experience is advantageous.
Hands-on lab work experience with image acquisition using industrial or digital imaging is advantageous.
Experience in material aware object representation such as Ref-Gaussian or Material-Informed GS is advantageous.
High level of commitment and team spirit.
Very good English skills, spoken and written.

What To Expect

Duration of the master's thesis project: 6 months.
Start date: ideally June 2026, with flexibility depending on availability.
EUR 1.027,40 gross per month for 20 hours per week based on the collective agreement, plus additional company benefits.
Opportunity to work on a real-world research challenge from collaborations with industrial partners.
Hands-on experience with cutting-edge imaging technologies and mentoring from AIT and TU Wien.

Please submit your application documents including CV, cover letter, relevant certificates, transcript of records and proof of identity online.

Apply now

Hauptstandort

Random Phone Number
randomemail@example.com

Ansprechpartner

.js-only-skeleton { display: none !important; }

Master Thesis "Material Aware Inline 3D Imaging"

In cooperation with TU Wien - Institute for Photogrammetry and Remote Sensing

Your Tasks

Acquire basic skills in inline optical 3D imaging for process control and automation.
Carry out a literature search and review on state-of-the-art optical detection and reconstruction of material properties.
Explore the potential of material aware Gaussian Splatting and related approaches or sensing methods like multispectral imaging for fast inline quality control.
Use the machine vision lab and a digital-twin Blender model of the lab setup to carry out experiments and collect datasets.
Depending on the thesis direction, expand the existing lab setup with multispectral sensing capabilities.

Your Qualifications

Ongoing master's studies at TU Wien in Geodesy and Geoinformation, Computer Vision/Image Processing, Computer Science, Physics, Mathematics or similar.
Good knowledge in computer vision and/or image processing.
Interest in machine vision, computer graphics and machine learning.
Experience in at least one programming language such as Python or C++; CUDA, OpenCV or Blender experience is advantageous.
Hands-on lab work experience with image acquisition using industrial or digital imaging is advantageous.
Experience in material aware object representation such as Ref-Gaussian or Material-Informed GS is advantageous.
High level of commitment and team spirit.
Very good English skills, spoken and written.

What To Expect

Duration of the master's thesis project: 6 months.
Start date: ideally June 2026, with flexibility depending on availability.
EUR 1.027,40 gross per month for 20 hours per week based on the collective agreement, plus additional company benefits.
Opportunity to work on a real-world research challenge from collaborations with industrial partners.
Hands-on experience with cutting-edge imaging technologies and mentoring from AIT and TU Wien.

Please submit your application documents including CV, cover letter, relevant certificates, transcript of records and proof of identity online.

Apply now

Hauptstandort

Random Phone Number
randomemail@example.com

Ansprechpartner

.js-only-skeleton { display: none !important; }

Master Thesis "Material Aware Inline 3D Imaging"

In cooperation with TU Wien - Institute for Photogrammetry and Remote Sensing

Your Tasks

Acquire basic skills in inline optical 3D imaging for process control and automation.
Carry out a literature search and review on state-of-the-art optical detection and reconstruction of material properties.
Explore the potential of material aware Gaussian Splatting and related approaches or sensing methods like multispectral imaging for fast inline quality control.
Use the machine vision lab and a digital-twin Blender model of the lab setup to carry out experiments and collect datasets.
Depending on the thesis direction, expand the existing lab setup with multispectral sensing capabilities.

Your Qualifications

Ongoing master's studies at TU Wien in Geodesy and Geoinformation, Computer Vision/Image Processing, Computer Science, Physics, Mathematics or similar.
Good knowledge in computer vision and/or image processing.
Interest in machine vision, computer graphics and machine learning.
Experience in at least one programming language such as Python or C++; CUDA, OpenCV or Blender experience is advantageous.
Hands-on lab work experience with image acquisition using industrial or digital imaging is advantageous.
Experience in material aware object representation such as Ref-Gaussian or Material-Informed GS is advantageous.
High level of commitment and team spirit.
Very good English skills, spoken and written.

What To Expect

Duration of the master's thesis project: 6 months.
Start date: ideally June 2026, with flexibility depending on availability.
EUR 1.027,40 gross per month for 20 hours per week based on the collective agreement, plus additional company benefits.
Opportunity to work on a real-world research challenge from collaborations with industrial partners.
Hands-on experience with cutting-edge imaging technologies and mentoring from AIT and TU Wien.

Please submit your application documents including CV, cover letter, relevant certificates, transcript of records and proof of identity online.

Apply now

Hauptstandort

Random Phone Number
randomemail@example.com

Ansprechpartner

Master Thesis "Material Aware Inline 3D Imaging"

AIT Austrian Institute of Technology GmbH

Master Thesis "Material Aware Inline 3D Imaging"

In cooperation with TU Wien - Institute for Photogrammetry and Remote Sensing

Your Tasks

Acquire basic skills in inline optical 3D imaging for process control and automation.
Carry out a literature search and review on state-of-the-art optical detection and reconstruction of material properties.
Explore the potential of material aware Gaussian Splatting and related approaches or sensing methods like multispectral imaging for fast inline quality control.
Use the machine vision lab and a digital-twin Blender model of the lab setup to carry out experiments and collect datasets.
Depending on the thesis direction, expand the existing lab setup with multispectral sensing capabilities.

Your Qualifications

Ongoing master's studies at TU Wien in Geodesy and Geoinformation, Computer Vision/Image Processing, Computer Science, Physics, Mathematics or similar.
Good knowledge in computer vision and/or image processing.
Interest in machine vision, computer graphics and machine learning.
Experience in at least one programming language such as Python or C++; CUDA, OpenCV or Blender experience is advantageous.
Hands-on lab work experience with image acquisition using industrial or digital imaging is advantageous.
Experience in material aware object representation such as Ref-Gaussian or Material-Informed GS is advantageous.
High level of commitment and team spirit.
Very good English skills, spoken and written.

What To Expect

Duration of the master's thesis project: 6 months.
Start date: ideally June 2026, with flexibility depending on availability.
EUR 1.027,40 gross per month for 20 hours per week based on the collective agreement, plus additional company benefits.
Opportunity to work on a real-world research challenge from collaborations with industrial partners.
Hands-on experience with cutting-edge imaging technologies and mentoring from AIT and TU Wien.

Please submit your application documents including CV, cover letter, relevant certificates, transcript of records and proof of identity online.

Apply now

Bewerben

.js-only-skeleton { display: none !important; }

Master Thesis "Material Aware Inline 3D Imaging"

In cooperation with TU Wien - Institute for Photogrammetry and Remote Sensing

Your Tasks

Acquire basic skills in inline optical 3D imaging for process control and automation.
Carry out a literature search and review on state-of-the-art optical detection and reconstruction of material properties.
Explore the potential of material aware Gaussian Splatting and related approaches or sensing methods like multispectral imaging for fast inline quality control.
Use the machine vision lab and a digital-twin Blender model of the lab setup to carry out experiments and collect datasets.
Depending on the thesis direction, expand the existing lab setup with multispectral sensing capabilities.

Your Qualifications

Ongoing master's studies at TU Wien in Geodesy and Geoinformation, Computer Vision/Image Processing, Computer Science, Physics, Mathematics or similar.
Good knowledge in computer vision and/or image processing.
Interest in machine vision, computer graphics and machine learning.
Experience in at least one programming language such as Python or C++; CUDA, OpenCV or Blender experience is advantageous.
Hands-on lab work experience with image acquisition using industrial or digital imaging is advantageous.
Experience in material aware object representation such as Ref-Gaussian or Material-Informed GS is advantageous.
High level of commitment and team spirit.
Very good English skills, spoken and written.

What To Expect

Duration of the master's thesis project: 6 months.
Start date: ideally June 2026, with flexibility depending on availability.
EUR 1.027,40 gross per month for 20 hours per week based on the collective agreement, plus additional company benefits.
Opportunity to work on a real-world research challenge from collaborations with industrial partners.
Hands-on experience with cutting-edge imaging technologies and mentoring from AIT and TU Wien.

Please submit your application documents including CV, cover letter, relevant certificates, transcript of records and proof of identity online.

Apply now

Hauptstandort

Random Phone Number
randomemail@example.com

Ansprechpartner

.js-only-skeleton { display: none !important; }

Master Thesis "Material Aware Inline 3D Imaging"

In cooperation with TU Wien - Institute for Photogrammetry and Remote Sensing

Your Tasks

Acquire basic skills in inline optical 3D imaging for process control and automation.
Carry out a literature search and review on state-of-the-art optical detection and reconstruction of material properties.
Explore the potential of material aware Gaussian Splatting and related approaches or sensing methods like multispectral imaging for fast inline quality control.
Use the machine vision lab and a digital-twin Blender model of the lab setup to carry out experiments and collect datasets.
Depending on the thesis direction, expand the existing lab setup with multispectral sensing capabilities.

Your Qualifications

Ongoing master's studies at TU Wien in Geodesy and Geoinformation, Computer Vision/Image Processing, Computer Science, Physics, Mathematics or similar.
Good knowledge in computer vision and/or image processing.
Interest in machine vision, computer graphics and machine learning.
Experience in at least one programming language such as Python or C++; CUDA, OpenCV or Blender experience is advantageous.
Hands-on lab work experience with image acquisition using industrial or digital imaging is advantageous.
Experience in material aware object representation such as Ref-Gaussian or Material-Informed GS is advantageous.
High level of commitment and team spirit.
Very good English skills, spoken and written.

What To Expect

Duration of the master's thesis project: 6 months.
Start date: ideally June 2026, with flexibility depending on availability.
EUR 1.027,40 gross per month for 20 hours per week based on the collective agreement, plus additional company benefits.
Opportunity to work on a real-world research challenge from collaborations with industrial partners.
Hands-on experience with cutting-edge imaging technologies and mentoring from AIT and TU Wien.

Please submit your application documents including CV, cover letter, relevant certificates, transcript of records and proof of identity online.

Apply now

Hauptstandort

Random Phone Number
randomemail@example.com

Ansprechpartner

.js-only-skeleton { display: none !important; }

Master Thesis "Material Aware Inline 3D Imaging"

In cooperation with TU Wien - Institute for Photogrammetry and Remote Sensing

Your Tasks

Acquire basic skills in inline optical 3D imaging for process control and automation.
Carry out a literature search and review on state-of-the-art optical detection and reconstruction of material properties.
Explore the potential of material aware Gaussian Splatting and related approaches or sensing methods like multispectral imaging for fast inline quality control.
Use the machine vision lab and a digital-twin Blender model of the lab setup to carry out experiments and collect datasets.
Depending on the thesis direction, expand the existing lab setup with multispectral sensing capabilities.

Your Qualifications

Ongoing master's studies at TU Wien in Geodesy and Geoinformation, Computer Vision/Image Processing, Computer Science, Physics, Mathematics or similar.
Good knowledge in computer vision and/or image processing.
Interest in machine vision, computer graphics and machine learning.
Experience in at least one programming language such as Python or C++; CUDA, OpenCV or Blender experience is advantageous.
Hands-on lab work experience with image acquisition using industrial or digital imaging is advantageous.
Experience in material aware object representation such as Ref-Gaussian or Material-Informed GS is advantageous.
High level of commitment and team spirit.
Very good English skills, spoken and written.

What To Expect

Duration of the master's thesis project: 6 months.
Start date: ideally June 2026, with flexibility depending on availability.
EUR 1.027,40 gross per month for 20 hours per week based on the collective agreement, plus additional company benefits.
Opportunity to work on a real-world research challenge from collaborations with industrial partners.
Hands-on experience with cutting-edge imaging technologies and mentoring from AIT and TU Wien.

Please submit your application documents including CV, cover letter, relevant certificates, transcript of records and proof of identity online.

Apply now

Hauptstandort

Random Phone Number
randomemail@example.com