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Paid Internship
Work Mode
Time Spent
Required Degree
Duration

11Open Positions

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  • Research Intern for Deep Generative Modeling

    Sony Europe
    Schlieren, Switzerland
    Found 2 months ago
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    German Aerospace Center (DLR)
    Braunschweig, Germany
    Found 2 weeks ago
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    Beyond Gravity
    Zürich, Switzerland
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    University of Applied Sciences and Arts of Southern Switzerland
    Mendrisio, Switzerland
    Found 3 weeks ago
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    German Aerospace Center (DLR)
    Braunschweig, Germany
    Found 3 weeks ago
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    Sabena Engineering
    Gosselies, Belgium
    Found 4 weeks ago
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    Airbus Helicopters
    Donauwörth, Germany
    Found 1 month ago
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    Airbus Helicopters
    Toulouse, France
    Found 1 month ago
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    Pratt & Whitney
    Rzeszów, Poland
    Found 1 month ago
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    Leonardo
    Brindisi, Italy
    Found 2 months ago
  • Stage 2026 - Bac Pro Aéronautique option structure : Ajusteur Monteur (ALL GENDER)

    Airbus
    Rochefort, France
    Found 2 months ago
  • ESA Graduate Trainee in Materials, Environments and Contamination Control

    European Space Agency - ESA
    Noordwijk, Netherlands
    Found 2 months ago

Research Intern for Deep Generative Modeling

Sony Europe
Found 2 months ago
Location
Schlieren, Switzerland
Duration (Months)
6 Months
Time
Not disclosed
Work Mode
Hybrid
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
2 months ago

Education

  • Master

Skills & Qualifications

Technical Skills

  • machine learning
  • deep learning
  • developing novel models or algorithms
  • programming skills for large-scale deep learning

Soft Skills

  • self-motivated
  • communication and presentation skills

Job Description

As a Research Intern, you will conduct novel and advanced research with internal members. You are expected to be self-motivated and have the ability to conduct and implement innovative ideas through internal collaborations. Our primary research interest include (but are not limited to): Efficient and/or scalable training/sampling of deep generative models Technologies for safe deep generative models, such as memorization mitigation/detection, concept erasing, and training data attribution Representation learning framework for multimodal generative models We expect the outcome of your research will be published as academic papers.

Requirements

  • Strong technical background in machine learning and deep learning
  • Experience in developing novel models or algorithms, with a track record of publishing papers at major conferences (e.g., NeurIPS, ICLR, ICML, CVPR, etc.)
  • Excellent analytical and programming skills for large-scale deep learning
  • Strong communication and presentation skills

Related Field

  • AI & Machine Learning

Related Subfield

  • Deep Learning

Languages

  • English

Nice to Haves

  • Diverse experience and knowledge in generative models, representation learning or general realm of deep learning
  • some experience in multiple modalities of deep learning, such as computer vision, natural language processing or audio
▶Apply Now

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