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1. Introduction:

Join our dynamic team in building a world-class presence in AI, Machine Learning, and an array of cutting-edge technologies. From Deep Learning to Robotics, Autonomous Systems to Security, we are at the forefront of innovation. This is your opportunity to contribute to groundbreaking projects in fields such as Computer Vision, Image Processing, Data Mining, and more.

2. Positions:

We welcome candidates from diverse backgrounds, spanning computer science, engineering, finance, and biology. Whether you're a first-year student or a seasoned professional, there are opportunities for internships, thesis positions, and collaborative work with our talented team. Embrace the chance to participate in machine learning conferences and even travel abroad. Conquer challenging tasks, gain invaluable experience, and pave the way for your future in AI.

3. Number of Candidates:

We're open to applications from candidates with varied experiences, and there's no limit to the number of positions available.

4. Requirements:

Strong fundamentals in programming and mathematics.
Proficiency in C/C++ and Python. Mastery in C++/C is a prerequisite.
Motivation and dedication to tackle challenging projects over an extended period (minimum 6 months).
Familiarity with motion capture, human cognitive behaviors, and motion analysis.
Deep understanding of human pose estimation and action recognition.
Basic knowledge of statistical machine learning.
Proficiency in Bayesian Inference and probabilistic graphical models.
Experience with frameworks such as Caffe, PyTorch, or TensorFlow.
Expertise in Computer Vision and Image Processing, including detection, segmentation, tracking, and deformation.
Interest in 3D reconstruction, real-time and embedded multiple cameras.
Understanding of machine learning evaluation methods.
Skills in optimization, attention, and regularization problems.
Knowledge of Deep Learning and Neural Networks like ResNet, AlexNet, etc.
Familiarity with CPU/GPU/TPU computing, distributed, and parallel computation.
Experience in supervised learning, unsupervised learning, and auto-machine learning.
Applied ML experience in areas such as automotive, medical applications, self-driving cars, robotics, food processing, quality control, and smart city technologies.
5. Time:

There are no constraints on the time commitment during project progress.

How to Apply?

Please send your CV directly to the provided email address.

International and National Olympic Awards or any National Challenge participation is a strong plus.

Note: We are open to collaborating with students involved in long-term thesis research. Contact us by email for further information.

WISDOM

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