Research Directions

1. Fine-tuning and training of protein language models based on the Transformer architecture;

2. Efficient mining of co-evolutionary information and integration of structural constraints for functional prediction, directed mutagenesis, and generative design;

3. Expansion of protein language models in downstream tasks, such as functional annotation, interaction prediction, and adaptive evolution modeling.

Job Responsibilities

1. Collaborate with the supervising mentor on topics related to protein language models; develop and implement relevant deep learning models for protein structure prediction, variant screening, or functional generation;

2. Work with relevant synthetic biology experimental platforms to advance experimental validation of model predictions and feedback learning;

3. Assist the team in applying for research projects and writing high-quality papers;

4. Guide research assistants and graduate students.

Application Conditions

1. Have obtained or are about to obtain a doctoral degree, with a background in fields including but not limited to bioinformatics, artificial intelligence, computational biology, structural biology, computational chemistry, etc.; PhD holders interested in AI for Science are welcome;

2. Be familiar with deep learning frameworks, with priority given to those with experience in language model fine-tuning or training, or in protein sequence analysis or structural simulation;

3. Have the ability to conduct independent research, with strong English reading and writing skills;

4. Demonstrate good academic ethics and a collaborative spirit, with a strong team orientation; preference will be given to applicants who can start full-time soon.

Application Method

Interested candidates should compile the following materials into a single PDF file and send it to:jinggang.lan@suat-sz.edu.cn, using“Postdoc Application - Name - Applying College - Research Group”as the email subject and attachment title:

(1)Personal resume (including list of published papers, project experience, etc.);

(2)Representative achievements (such as the first page of papers in PDF format)

(3)A brief research plan or statement of interests.