How to Apply

Check out our current & past 3DI members – are you our next one?

We always look for strong and passionate people to join the 3DI team!

PhD: We have 3x funded positions (description below); in exceptional case 1 might be PostDoc
PostDoc: We look for researchers that come with/apply for own funding (e.g. MSCA, ELIDEK)
Diploma Thesis: We look for highly-motivated AUTh students that want to grow in our field

→ Please fill in this Google Form carefully and completely!

Applications and interviews are handled continuously and on a rolling basis — please apply early for best chances. In case there is a good fit, we will get back to you for a first Zoom call, and potentially to arrange interviews. Otherwise, due to the volume of applications, we regret that we may not be able to respond individually to every applicant.

PhD/Researcher collaborations

Are you already a PhD or Researcher at another institute/company and are interested in a collaboration for your work? Drop me a line via e-mail!

3 PhD positions @AUTh (ERC funded) – Start within 2026

Do you want to help computers see, understand, and assist us, humans, in our everyday life? Are you excited with artificial intelligence (AI), mixed reality (MR), 3D spatial computing, 3D human avatars, 3D reconstruction and synthesis, and world models for avatars / robotics / physical AI? Do you aspire to conduct internationally-visible research? We search for a strong PhD candidate to push together the state of the art!

Context

Humans constantly interact with objects, spaces and other humans to perform tasks. This is reflected in the photos and videos that we upload on Facebook, Instagram, YouTube, or that we capture through smart glasses (Microsoft’s HoloLens, Meta’s Aria). Our long-term goal is to develop human-centered AI that accurately perceives humans from images while performing tasks, and assists them in these. This is important for Ambient Intelligence, Virtual Assistants, World models for Avatars / Robotics / Embodied AI, Human-Computer and Human-Robot Interaction, and Augmented / Virtual Reality (AR/VR).

To this end, we first need to “make sense” of the observed scene, i.e., to model how people, objects, and spaces look, to estimate their shape and pose, to infer their semantics and spatial relationships, and to do all of these in 3D, as our bodies and world are also 3D. Think of this as “mirroring” the observed scene, with the humans and objects contained in it, to a “replica” virtual scene with 3D humans and objects. This holistic 3D reconstruction (or 4D over time) endows computers with the ability to recognize what is in the scene, infer the state of humans and objects, and analyze the semantic and spatial configuration of the observed scene and action.

Although for humans this perceptual capability seems effortless, for computers this has proven to be hard. Challenges exist at all levels of abstraction, from the ill-posed 3D inference from 2D images, to the semantic interpretation of it. Among others, this project involves challenges like:

Reconstructing deformable 3D human bodies and hands from single-/multi-view images;
Reconstructing additionally 3D physical objects from single-/multi-view images;
Dealing with the strong occlusions during realistic human-object interactions;
Representing (possibly through “learning”) the spatial relations (e.g., proximal distances, contact, penetration) and semantics (e.g., affordances) of human-object interactions;
Accounting for the low-data regime – possible directions: collecting novel datasets for training and evaluation, weakly-supervised approaches, optimization-based approaches;
Extending 3D reconstruction over time (4D);
Potentially using the above to develop novel pose/motion generation methods.

These are hot research problems for both academia and industry. For representative papers see our preprints and publications.

Each project in this PhD can be tailored to the aligned interests between the PhD candidate and the advisors. The goal is fundamental research to push the state of the art, publish at top-tier venues, release data and code useful for the community, and introduce new research problems.

What are you going to do?

Your tasks and responsibilities will be to:

Develop and evaluate new methods at the intersection of (3D) computer vision, computer graphics and machine learning, within the project context described above;
Collaborate with other researchers in the 3DI team, as well as (inter-)nationally;
Complete and defend a PhD thesis within the funding period (3 years, with potential extension for a 4th year);
Regularly present intermediate research results at top-tier international conferences;
Provide a reviewing service for top-tier conferences;
Help write proposals that secure computational resources (e.g. EuroHPC) and funding;
Develop exciting demos for both the research community and for public outreach;
Assist in teaching activities, e.g., lectures, labs, co-advising BSc/MSc students.

Advising

You will be co-advised by Dimitris Tzionas (DT). We work on the intersection of (3D) computer vision, graphics and machine learning. We publish at top international venues (CVPR, ICCV, ECCV, SIGGRAPH/TOG, IJCV, TPAMI). We have expertise on statistical 3D models for human bodies/hands, 3D human shape/pose and (inter-)action understanding from images, and 3D synthesis. We currently co-organize the 3DV 2027 conference that brings together top international researchers of our field. A paper co-authored by DT was a best-paper finalist at CVPR 2022. The surrounding 3DI team of 5 PhD students (and growing) are available for interactions and possible collaboration. Our strong international network (ex-labmates, ELLIS society and beyond) can also lead to potential collaborations and/or internships.

What do you have to offer?

Your experience and profile – you check several/most of the following boxes:

A MSc degree (or equivalent 5y Diploma) in Artificial Intelligence, Computer Science, Electrical and Computer Engineering, Mathematics, or a closely related field;
A strong background in (3D) computer vision, graphics and machine learning;
Excellent hands-on programming skills (preferably in Python and PyTorch);
Solid mathematics skills (especially in statistics, calculus, linear algebra, 3D geometry);
Strong communication, presentation and writing skills and excellent command of English;
Working successfully both independently and in a team;
Being highly self-motivated, creative, and thinking both critically and outside the box.

Any of the following is a plus, but not necessary:

Hands-on experience with: AR/VR/MR/XR, 3D game/physics engines, 3D geometry processing, SLAM, numerical optimization (e.g., ceres), neural networks (e.g., PyTorch), robotics (e.g., control, path planning), GPU programming (e.g., CUDA);
Scientific publications, internships, industrial experience, contributions in open-source projects, participation in (inter-)national student competitions (e.g., robocup).

Any questions?

Do you have any questions or do you require additional information? Please contact Dimitris Tzionas.

Job application

→ Please fill in this Google Form carefully and completely!