A unique opportunity for a unique, inspiring and creative internship program.

Find yourself actively involved from day one.

We invest in diverse fields of emerging research. New challenging topics arise continuously.

Get training and supervision via a creative collaboration that leads to impactful research projects that maximize your potential.

Take advantage of our expertise, prior academic and industrial experience  to open new perspectives.



Types of Internships

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ATLAS Internship (Open call)

We support internship programs via ATLAS, the main students’ portal for internships. If you are a final year student and eligible for a funded internship you may apply via your personal student account as well as our website.

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Diploma Thesis Interns

We are glad to offer very selectively co-supervision services in collaboration with academic departments and/or research institutions, after specific invitation from the academic side, providing ourselves intensive support given our expertise and prior academic/industrial experience.

Note (Not Open): We currently only consider such cases for very promising candidates given specific screening and recommendations  by their supervisors in academia/research institutions. 

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Research Trainees

We are open to fund long term research trainees recommended and sourced  by the academia, in  joint research projects,  PhD co-supervision towards innovative and impactful new directions.

Note (Not Open): We  currently only consider such cases for extra-ordinary promising candidates after invitation from an academic partner and given specific screening and recommendations  by their supervisors in academia/research institutions.

Program Overview

Enhance your work with high-end technical, state-of-the-art research experience.


Mentoring and supervision  in a custom tailored scientific pipeline for each intern lead to successful self-contained internship.


Acquire research and industrial experience from professional ML/ Software engineers/ researchers depending on the project. 


Emerging novel research projects

Find yourself working in novel research projects acquiring state-of-the-art research and ML software experience which will guide you in a well prepared and inspiring journey.

Supervision. Training. Support. Network.

Continuous support, training and close supervision by experienced, skilled  professionals.

Soft skills and culture

Teamwork, planning, time management, problem solving, creativity and group intelligence will thrive by working with the rest of the group while growing within our team.


Inspiring environment

Great environment both on site and virtually via online meetings, reading groups and milestone open presentations.



Indicative timeline and description for the case of ATLAS 3-months short term internship journey.

  • Join the team

    The whole deeplab team welcomes you ! Join a specific subgroup to collaborate with, having a main supervisor, a group of collaborators, plus a high-level personal/career development mentor. 

  • Introduction

    Learn about the area of work. We adapt a project in your skills and interests. Get an initial presentation and training workshop on the main tasks, challenges, resources and expected project outcomes. Cultural training is cultivated all the way since day one. 

  • Regular creative meetings

    Meaningful regular meetings with experts, your supervisor, as well as your peers in sub-groups of interest will support you so that you learn how to plan your way within this journey. 

  • Progress monitoring

    High level discussion with senior mentors once per 2-3 weeks depending on the progress. We design by construction your internship so that we can guarantee that your work leads to  fruitful and interesting outcomes.

  • Milestone presentations

    Learn to plan, document, and present your work to the rest of the team. We work closely with you in order to train you with all skills required to interact with scientific/engineering teams, and plan your way along the whole journey. 

  • Final open presentations

    Finally you shall present the R&D fruits of your work in workshops that deeplab organizes together with other open presentations, giving the chance in real-working experience to get feedback, brainstorm and  be social, within  a highly demanding R&D industrial environment while cultivating academic values.


The team consists of bright, enthusiastic and motivated final year students who share with us the passion for challenging problem-solving applied to tough research/industrial problems.

Diploma Thesis Interns


Orestis Papanikolaou, Diplome Thesis Intern 

Research focus: "In the wild long-tail visual relationship detection"

Undergraduate student at Computer Engineering & Informatics, 5-year degree (UPatras, expected 2021). Currently working on thesis about representation learning with Graph Neural Networks on graph data. Interested in Machine Learning in general, as well as in Recommendation Systems  and in fusion of Computer Vision with Natural Language Processing.


Zacharias Anastasakis, Diploma Thesis Intern 

Research focus: "Self-supervised learning for visual relationships"

Electrical & Computer Engineering, NTUA. Zacharias involved in several projects related to machine learning in the context of the academic tasks and is looking forward to tackling real-world problems. Highly interested in Machine Learning, Deep Learning and biomedical applications.


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Nikos Bazotis, Diploma Thesis Intern 

Research focus: "Research Diploma thesis Topic on ML/Deep learning Enhanced Cybersecurity"

Electrical & Computer Engineering (NTUA).Master thesis is on the topic of Human Activity Recognition for security surveillance that is supervised by E.Spyrou , T.Giannakopoulos at NCSR 'Demokritos' . The task relies on anomaly behavior detection from security cameras in public spaces. Nikos is interested mostly in the field of deep learning and computer vision with application to daily life tasks


Alexandros Benetatos, Diploma Thesis Intern 

Research focus: "Weakly supervised visual relationship detection"
Electrical & Computer Engineering 5-year degree (NTUA, 2020). Master thesis is on the topic of visual relationship detection and is being co-supervised by P. Maragos at NTUA and by M. Diomataris and V. Pitsikalis at Deeplab. Alexandros has been a member of NTUA’s Prometheus Eco Racing team developing software and hardware for prototype electric vehicles and winning the first prize in the "Safety Award'' category of Shell Eco Marathon in 2018. Interested in deep learning, fusion of visual and linguistic cues for tasks related to image understanding and reasoning.

Research Trainee Interns


Manos Zaranis, Long-term Research Trainee Intern 

Research focus: "Unseen visual relationship detection"

Electrical & Computer Engineering 5-year degree (NTUA, 2020). Master thesis was on the topic of dialogue generation using generation-based models and was co-supervised by APotamianos at NTUA and by N. Katsamanis. Manos is interested in deep learning and specifically in natural language processing generation tasks or multimodal tasks combining computer vision and natural language processing. When Manos is not coding, he enjoys travelling, windsurfing and going to the theatre.

Mary Parelli, Long-term Research Trainee Intern 

Research focus: "Visual common sense reasoning"

Electrical & Computer Engineering 5-year degree (NTUA, 2020). Master thesis was on the topic of sign language recognition and human pose estimation and was supervised by P. Maragos at NTUA. Mary was also a co-founder of a fintech start-up that aimed to deliver an automated shopping experience. Her main focus lies in the field of deep learning and computer vision. Highly interested in the fusion of computer vision and language modeling as well as visual understanding and reasoning.

Alumni Interns


Ioanna Gogou, ATLAS Intern

Project title: "Monte Carlo Dropout for Virtual Screening with Graph Neural nets"

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Angelos Ragkousis, ATLAS Intern 

Project title: "Multi-modal network for virtual screening"

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Nikos Bazotis, ATLAS Intern

Project title: "An investigation on  training datasets for binding affinity prediction networks"


Orestis Papanikolaou, ATLAS Intern

Project title: "Implementation of "Knowledge- Embedded Routing Networks"


Zacharias Anastasakis, ATLAS Intern 

Project title: "Use of virtual node for binding affinity prediction graph neural networks"

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Alexandros Liapatis, ATLAS Intern 

Project title: "Snapshot ensembles for virtual screening"

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Sotiris Karapiperis, ATLAS Intern 

Project title: "Few/Zero shot Visual Relationship Detection using VAEs."

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Iason Christoulakis, ATLAS Intern 

Project title: "Leveraging large-scale pretraining for Visual Relationship Detection"


Marios Glytsos, ATLAS Intern 

Project title: "Visual Common sense Reasoning"

Recent collaboration with


My internship in Deeplab was a “rite of passage” kind of experience for my Machine Learning journey. I was mentored by passionate and talented experts who encouraged me every step of the way and challenged me to try new ideas. I gained tons of knowledge, while at the same time Ι understood how much I have yet to learn.


Ioanna Gogou

As an intern coming to Deeplab, I couldn't imagine finding an environment like that. Everyone in the company welcomed me and helped me get started in any way they could. And although they manage to excel in many Deep Learning areas and be professional in their work, it still feels more like a big family. If anything, Deeplab's superpower is its people.


Alexandros Benetatos
Diploma Thesis Intern

ApPLy to Become an intern

  1. Interested in applying for an internship in Deeplab? Express your interest by sending your application together with your CV.
  2. Students eligible for a placement, please consider applying also via your ATLAS account.
  3. The main way for someone to enter the internships' journey with us is the short time internship track.
  4. Short term ATLAS internships  are currently the only internship case  that is open (see notes above).
  5. This is the best way to get to know each other, after a specific screening process, and could potentially lead to further long term internships and collaborations.