-
Models. Experience with deep learning frameworks such as PyTorch or TensorFlow. Proficiency in programming languages including C/C++, Python, Java, and Go. Familiarity with Digital Content Forensics
-
verbal, written communication skills In-depth knowledge of deep learning, specifically VLM models, computer vision techniques (e.g., open vocabulary object detection, model distillation, VQA, test-time
-
opportunities within the company. Responsibilities Develop and implement advanced computational and machine learning strategies, including deep learning, graph-based methods, and probabilistic modeling
-
; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
-
required. Substantial experience in machine learning, Python and R programming, and familiarity with deep learning packages (e.g., TensorFlow, Keras, or PyTorch) are essential. Additional Qualifications
-
program, providing them with a deep understanding of the field and hands-on experience in informatics research. In addition to the primary informatics and research responsibilities, there is the potential