Game Simulation Engineer - Fresh Grad

at  COGNOSPHERE PTE LTD

Who Are We?
HoYoverse is committed to providing immersive virtual world experiences to players around the world. We have brought fans popular games including Genshin Impact, Honkai: Star Rail, Honkai Impact 3rd, Tears of Themis, and Zenless Zone Zero, as well as a wide range of entertainment content.
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Community is at the heart of everything we do. We are devoted to engaging fans and fostering an enthusiastic and inclusive global community that provides access and encouragement for people to share their passion for ACG (Animation, Comics, and Games) through their own creativity and skills.
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Pushing the boundaries of imagination, we consistently explore cutting-edge game development technologies, and have accumulated leading technical capabilities in cel shading, cloud gaming, and other fields.
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In the future, we will continue to expand our content production, technology research, and publishing duties through operations in offices in Singapore, Montreal, Los Angeles, Tokyo, Seoul, and other areas.
When you apply to a position with HoYoverse, we will process your personal data. To learn more about how we process your data, we encourage you to review our comprehensive Global Applicant and Candidate Privacy Policy. This policy provides detailed insights into how your information is collected, used, and protected throughout the application process.

What You Will Do:

• Participate in the development and performance optimization of high-quality real-time physically-based simulation modules (cloth and hair) for pre-research projects.
• Explore pre-computed simulation acceleration methods (data-driven/deep learning) and body-driven subspace simulation algorithms.

What We Are Looking For:

• Bachelor’s degree or above in computer graphics, with relevant research experience in physically-based simulation, a solid foundation in numerical computation, and familiarity with numerical algorithms for cloth and hair simulation is preferred.
• Proficient in C++ and GPU parallel computing programming.
• Willing to continuously advance research in the frontier direction of physical simulation.
• Willing to industrialize relevant work from GDC/SIGGRAPH.

Bonus Points:

• Published relevant SIGGRAPH/TOG papers in the field of physical simulation.
• Proficient in a shading language (GLSL, HLSL, etc.) and have experience in developing physical solvers in game engines (Unity/Unreal).

Application Instructions:

• Artworks serve as a significant showcase of your skills. Please submit a selection of your most satisfying recent works.
• The application submission attachment size limit is 500 MB. Make sure your portfolio’s overall file size does not exceed this limit. We do not recommend submitting your portfolio via cloud storage links.
• For static images, submit in JPG or PNG format. Avoid over-compression to maintain optimal image quality. Do not submit source files.
• For simulation and sequential frames, submit them in MP4 or AVI format. Ensure appropriate compression without compromising visual quality. Do not submit source files.
• For simulation works, submit via screenshots or videos. Do not submit project files.
• If you have profiles on platforms such as Weibo, Lofter, Pixiv, ArtStation, Bilibili, etc., you can add respective links in your resume to provide a better understanding of your work.
• If applicable, please provide details of your personal gaming experience and any relevant works. Your gaming experience should include the names of games you have played, the duration of gameplay, and any notable achievements you have earned.

We are an equal opportunity employer that believes diverse backgrounds are key to bringing our concepts to life. If you’re looking to play a key role in creating the best immersive virtual world experience for our users, we invite you to join our team

• Participate in the development and performance optimization of high-quality real-time physically-based simulation modules (cloth and hair) for pre-research projects.
• Explore pre-computed simulation acceleration methods (data-driven/deep learning) and body-driven subspace simulation algorithms