Research Fellow (Computer Science and Engineering)

Updated: about 1 month ago
Location: Singapore,
Job Type: FullTime

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.

  • Familiarity with knowledge transfer techniques and compositionality in machine learning is highly desirable.
  • 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.

  • Passion for applying machine learning algorithms to real-world problems, particularly in domains with limited data such as drug discovery.
  • Effective communication skills and ability to convey complex technical concepts to both technical and non-technical stakeholders.

We regret that only shortlisted candidates will be notified.
 

Hiring Institution: NTU



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