start:academic_prerequisites [Extended Cinematography]

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====== ACADEMIC PREREQUISITES ======

===== Mathematics and Computer Science Background =====

Applicants should have a strong academic background in both Mathematics and Computer Science. A Bachelor's degree in either field is welcome, provided the applicant demonstrates solid proficiency in the other.

> **Applied Mathematics**
> A solid understanding of linear algebra, partial derivatives, and multiple integrals for mathematical modeling is required. Familiarity with statistics and signal/image processing concepts, especially Fourier theory and basic filtering techniques. While many software libraries implement these functionalities, a firm grasp of the underlying theories and their practical applications is important.

> **Computer Science**
> Applicants should have completed at least one course covering Algorithms and Data Structures and demonstrate programming proficiency, particularly in C++ and Python.




===== Portfolio, GitHub & Personal Projects =====

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Applicants are **strongly encouraged** to provide evidence of their technical, scientific and creative work.

  * **Online Portfolio (highly recommended):** Showcase your best technical, scientific or creative projects through visual results, videos, interactive demonstrations or research work. Clearly identify your personal contributions.
  * **GitHub or Equivalent (recommended):** Share code repositories demonstrating programming skills, software engineering and experimentation.
  * **Personal & Academic Projects:** University projects, research prototypes, creative work, hackathons or independent developments.

The quality and relevance of your work matter more than the number of projects.
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===== Internships & Professional Experience =====

> **Previous internships, research activities and professional experience are highly valued.**

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Experience in computer graphics, computer vision, AI, software engineering, VFX, animation, video games, filmmaking or other related technical and creative fields is particularly relevant.

Applicants should highlight:

  * **Internships and professional placements**, including their duration and responsibilities.
  * **Research experience**, whether academic or industrial.
  * **Technologies and tools** used in real projects.
  * **Concrete achievements**, technical challenges and individual contributions.

Previous professional experience is a significant asset, but **is not mandatory for admission**.

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