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The School of Computer Science and Engineering (SCSE) invites applications for the position of Research Fellow.
Key Responsibilities:
Conduct independent research in the filed of knowledge continual transfer and multimodal compositionality based on LLM, including multi-modal compositionality, compositional reasoning with commonsense knowledge, and LLM-based compositionality understanding and reasoning.
Develop algorithms for continuous knowledge transfer and compositional reasoning to facilitate efficient learning of new tasks.
Collaborate with a research group member to design and implement algorithms aimed at enhancing machine intelligence through knowledge transfer and compositionality.
Apply developed algorithms to real-world applications with sparse data
Stay abreast of the latest research in machine learning, artificial intelligence, and related fields to incorporate new techniques into algorithm development efforts.
Help supervise PhD, master and undergraduate students.
Job Requirements:
PhD degree in computer science, software engineering, mathematics, or a related field.
Strong background in multimodal learning, natural language processing, domain adaptation, and knowledge graph, particularly in algorithm development and implementation.
Good publication track record is a must.
Proficiency in programming languages such as Python, and experience with machine learning libraries (e.g., TensorFlow, PyTorch).
Excellent problem-solving skills and ability to work independently as well as part of a team.
We regret that only shortlisted candidates will be notified.
Hiring Institution: NTU
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