The School of Computer Science and Engineering (SCSE) is seeking a dedicated Research Associate in Computer Science and Engineering with a focus on advancing the fields of diffusion models and machine generalization.
This role requires a passion for innovation, the ability to work effectively in a collaborative environment, and a commitment to contributing to groundbreaking discoveries in computer science and engineering.
Key Responsibilities:
Collaborate closely with the Principal Investigator (PI) to design, implement, and analyze novel research projects.
Conduct high-quality research, developing new algorithms and models, and publishing findings in top-tier conferences.
Formulate the machine generalization problem in light of recent advancements in foundation models.
Design algorithms that improve diffusion model generalizations.
Collect or consolidate data to validate the designed algorithm.
Communicate research outcomes through papers or presentations.
Job Requirements:
Master's degree in computer science/engineering
Experienced in PyTorch or Tensorflow
Relevant publication regarding machine generalization or diffusion model is preferred.
Proficient in programming languages and frameworks relevant to machine learning, specifically Python and PyTorch.
Demonstrated publication record in top-tier conferences such as NeurIPS, ICML, CVPR, or similar.
Proven experience in designing, implementing, and evaluating algorithms and models, particularly in diffusion models and machine generalization.
Strong analytical and problem-solving skills, with a solid foundation in mathematics and statistics.
Ability to work independently and collaboratively in a research environment, with excellent communication skills for presenting research findings.
Strong background in machine learning, deep learning, or a related field, and exhibit a proven track record of research excellence and publication in reputable venues
We regret that only shortlisted candidates will be notified.
Hiring Institution: NTU
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