中国香港中文大学深圳分校人工智能学院Satoshi招聘Nakamura项目 博士后

博士后 - 人工智能学院Satoshi Nakamura项目 (Ref.PR2025/230/01)
截止日期: 2025-12-31 人工智能学院

Position title: Postdoctoral Researcher (Speech & Language Processing)

Lab/Unit: Spoken Language Communication (SLC) Lab, School of Artificial Intelligence (SAI), The Chinese University of Hong Kong, Shenzhen (CUHK Shenzhen)

Location: Shenzhen, China

Appointment: Full time; 24 month initial term with possibility of renewal

Start date: Flexible (target window: by Dec. 2025)

About the lab

The SLC Lab advances speech and multilingual communication with a focus on simultaneous speech translation (SimulST), LLMbased S2T/S2ST, simultaneous policy learning (RL/DPO), streaming alignment (CIF/monotonic attention/Transducer), and multimodal LLMs. We work within CUHK Shenzhen s rapidly growing School of Artificial Intelligence (SAI) and collaborate with international partners, supported by modern GPU resources and large scale multilingual corpora.

Research themes (illustrative)

1. Simultaneous Speech Translation (SimulST): quality latency tradeoffs; read write/simultaneous policies via RL/DPO; dynamic prompts and timing control; evaluation with AL/ATD.

2. Streaming ASR/ST & Alignment: RNNT/Transducer, monotonic attention, CIF, segmentation; codeswitching and lowlatency decoding.

3. SpeechtoSpeech Translation (S2ST) & TTS/Voice: neural codecs, expressive prosody, crosslingual synthesis/editing.

4. Multimodal & LLMbased Speech/NLP: instructiontuned LLMs, retrievalaugmented speech translation, safety and evaluation for spoken LLMs.

5. Robustness & LowResource: noise/reverberation/accent robustness, data selection/augmentation, privacy aware modeling.

6. Machine Speech Chain: joint ASR TTS modeling and data bootstrapping.

Responsibilities

1. Lead original research aligned with the themes above; formulate hypotheses and design rigorous experiments/ablations.

2. Build reproducible pipelines (PyTorch/JAX; Hugging Face; ESPnet/Fairseq/NeMo/SpeechBrain).

3. Author and present papers at ACL/EMNLP/AAAI/ICLR/ICASSP/INTERSPEECH/TASLP.

4. Mentor graduate/undergraduate students and coordinate collaborations within CUHK Shenzhen and with external partners.

5. Contribute to grant proposals, datasets, and open source/community releases as appropriate.

Minimum qualifications

1. Ph.D. in EE/CS/Computational Linguistics or related field (by start date).

2. Demonstrated excellence via publications at top tier AI conferences in speech/NLP/ML.

3. Strong programming skills (Python) and experience with modern deep learning frameworks.

4. Excellent scientific communication in English.

Desired qualifications

1. Experience with SimulST/read write policies, RL/DPO/RLHF, CIF/CTC/monotonic attention, multilingual and lowresource speech, evaluation (COMET, AL/ATD, WER/TER), robustness/accent/noise, prosody/voice, machine speech chain, and largescale training.

2. Project leadership and mentoring experience; familiarity with MLOps and reproducibility practices.

Compensation and support

1. Competitive salary commensurate with experience per CUHK Shenzhen policies.

2. Benefits according to university policy; conference travel support; access to internal compute/GPU clusters.

How to apply

Send a single PDF to snakamura@ containing:

1. CV (with publications)

2. Research statement (1 2 pages)

3. Up to three representative publications

4. Names and emails of 2 3 referees

Application review begins 15 Oct. 2025 and will continue until the position is filled.

For inquiries, please contact snakamura@.

Inclusive Environment

CUHK-Shenzhen and the SAI/SLC community value diversity, equity, and inclusion. All qualified applicants are encouraged to apply.

Additional notes (as applicable)

1. Work mode: Onsite.

2. Visa sponsorship: May be available in accordance with university policies and local regulations.

3. Security/export control: Final offers may be subject to relevant compliance checks.

For details, please see below. ah***com[点击查看]