The Bosch Group operates in most countries in the world. With over 400,000 associates, a career at Bosch offers a chance to grow an exceptional career in an environment that values diversity, initiative and a drive for results. We are looking for research interns (spring/summer/fall 2023) to join our research team in developing new machine learning/deep learning algorithms for various real-world applications of AI, including but not limited to: self-supervised learning, foundation models, zero/few-shot learning, adversarial robustness, computer vision, semantic segmentation, deep probabilistic modeling, and physics-based machine learning. By choice, we are committed to a diverse workforce – EOE/Protected Veteran/Disabled. All your information will be kept confidential according to EEO guidelines.

UNITED STATES: AMD Xilinx is an equal opportunity and affirmative action employer. Applicants and employees are treated throughout the employment process without regard to race, color, religion, national origin, citizenship, age, sex, marital status, ancestry, physical or mental disability, veteran status or sexual orientation. The information requested here is used only in compliance with US Federal laws and is not gathered for employment decisions. Responses are strictly voluntary, and any information provided will remain confidential. If you choose not to "self-identify", you will not be subject to any adverse treatment.

Today, we stand at the beginning of the AI computing era, ignited by a new computing model, GPU deep learning. This new model--where deep neural networks are trained to recognize patterns from massive amounts of data--has shown to be deeply effective at solving some of the most complex problems in everyday life. In this context, we are looking for a Rendering & Machine Learning Research Intern. You will be working with us on investigating the application of deep- and other machine-learning techniques to physically based rendering--the synthesis of realistic images by simulating the propagation of light through the virtual world. We leverage machine learning to increase the efficiency and quality of rendering algorithms with the ambitious eventual goal of a photorealistic real-time rendering engine.

The idea has appeared in my head during a talk given by an Artificial Intelligence expert, Alejandro Saucedo, at my university. It felt really exciting: there was a huge amount of students interested in AI and there was no study group like that at my Uni. What I was waiting for then? That was the beginning of the story of how creating a study group boosted my knowledge about AI and helped me in getting a summer internship in Machine Learning. I have never suspected that it will have such a big impact on me and on students who joined the group.