Artificial Intelligence

MERL is looking for a highly motivated and qualified intern to work on deep learning methods for detection and pose estimation of objects using vision and tactile sensing, in manufacturing and assembly environments. This role involves developing, fine-tuning and deploying models on existing hardware. The method will be applied for robotic manipulation where the knowledge of accurate position and orientation of objects within the scene would allow the robot to interact with the objects. The ideal candidate would be a Ph.D. student familiar with the state-of-the-art methods for pose estimation and tracking of objects. The successful candidate will work closely with MERL researchers to develop and implement novel algorithms, conduct experiments, and publish research findings at a top-tier conference. Start date and expected duration of the internship is flexible. Interested candidates are encouraged to apply with their updated CV and list of relevant publications.

Required Specific Experience

• Prior experience in Computer Vision and Robotic Manipulation.
• Experience with ROS and deep learning frameworks such as PyTorch are essential.
• Strong programming skills in Python.
• Experience with simulation tools, such as PyBullet, Issac Lab, or MuJoCo.

MERL is excited to announce an internship opportunity in the field of Quantum Machine Learning (QML) and Quantum AI (QAI). We are seeking a highly motivated and talented individual to join our research team. This is an exciting opportunity to make a real impact in the field of quantum computing and AI, with the aim of publishing at leading research venues.

Responsibilities:

• Conduct cutting-edge research in quantum machine learning.
• Collaborate with a team of experts in quantum computing, deep learning, and signal processing.
• Develop and implement algorithms using PyTorch and PennyLane.
• Publish research results at leading research venues.

Qualifications:

• Currently pursuing a PhD or a post-graduate researcher in a relevant field.
• Strong background and solid publication records in quantum computing, deep learning, and signal processing.
• Proficient programming skills in PyTorch and PennyLane are highly desirable.

What We Offer:

• An opportunity to work on groundbreaking research in a leading research lab.
• Collaboration with a team of experienced researchers.
• A stimulating and supportive work environment.

If you are passionate about quantum machine learning and meet the above qualifications, we encourage you to apply. Please submit your resume and a brief cover letter detailing your research experience and interests. Join us at MERL and contribute to the future of quantum machine learning!

We are on the lookout for passionate and skilled interns to join our cutting-edge research team focused on developing efficient machine learning techniques for sustainability. This is an exciting opportunity to make a real impact in the field of AI and environmental conservation, with the aim of publishing at leading AI research venues.

What We're Looking For:

• Advanced research experience in generative models and computationally efficient models
• Hands-on skills for large language models (LLM), vision language models (VLM), large multi-modal models (LMM), foundation models (FoMo)
• Deep understanding of state-of-the-art machine learning methods
• Proficiency in Python and PyTorch
• Familiarity with various deep learning frameworks
• Ph.D. candidates who have completed at least half of their program

Internship Details:

• Duration: approximately 3 months
• Flexible start dates available
• Objective: publish research results at leading AI research venues

If you are a highly motivated individual with a passion for applying AI to sustainability challenges, we want to hear from you! This internship offers a unique chance to work on meaningful projects at the intersection of machine learning and environmental sustainability.