Data Science Intern

Post-Graduates (Final Year Students - Master / PhD Program) with strong passion and understanding of Deep Learning (DL), Machine Learning (ML), and Computer Vision (CV). Good knowledge and understanding in machine learning, deep learning, image processing / computer vision. Knowledge on Image segmentation is a MUST. Strong proficiency in Python programming and debugging, associated libraries like OpenCV, PyTorch, PyQt, GUI, NumPy, Scikit-learn, etc. Self-driven personality with the team-work mindset and self-reliant working style. Previous relevant works in image segmentation, UNET, SAM, is a big plus. Our commitment We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees. Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. ‘On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex' you'll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.