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.
