What will you discover next?

The Tan Lab at NYU is recruiting a postdoctoral fellow to develop computational approaches for studying gene regulation and its implications for human health. Our research combines machine learning, biological mechanisms, and large-scale data to understand how regulatory elements in our genome control transcription factors, 3D genome organization, and transcription. We are recruiting PhD graduates who share the same passion for the following research areas:

1. 3D genome organization and transcription factors.

2. Transcriptional regulation and its role in development and disease.

3. Genomic foundation models and synthetic design of biological sequences.

As a postdoctoral fellow, you will conduct independent research projects and develop machine learning approaches to answer questions in the areas of interest listed above (Please indicate in the application if your interests are relevant but not listed). We are looking for computational researchers with extensive experience building ML models who want to contribute to the future of genomics research.

Qualifications:

Required: PhD in computational biology, computer science, electrical engineering, statistics, or other technical fields. A first-author publication related to ML in a conference or journal. Experience in designing machine learning algorithms and model architectures.

Preferred: A first-author publication related to biology and ML. Experience building generative ML models (e.g. diffusion, flow matching). Familiarity with sequencing data and bioinformatics.

To apply:

Required application materials include a cover letter, CV, representative publication, and a code sample. In your cover letter, describe your background, motivation to join our group, and your potential contribution. When you are ready, please submit your application through this portal: Postdoctoral Fellow at Tan Lab. We will review each application carefully and deprioritize applications generated with AI. We will do our best to respond to each applicant but may not be able to if we receive too many requests.

The Tan Lab at NYU is recruiting a postdoctoral fellow to develop computational approaches for studying gene regulation and its implications for human health. Our research combines machine learning, biological mechanisms, and large-scale data to understand how regulatory elements in our genome control transcription factors, 3D genome organization, and transcription. We are recruiting PhD graduates who share the same passion for the following research areas:

1. 3D genome organization and transcription factors.

2. Transcriptional regulation and its role in development and disease.

3. Genomic foundation models and synthetic design of biological sequences.

As a postdoctoral fellow, you will conduct independent computational research projects to develop or apply machine learning approaches to identify new biological insights related to the areas of interest listed above (Please indicate in the application if your interests are relevant but not listed). We are recruiting biologists who want to transform biological mechanisms into machine learning models.  We welcome biologists with genomics background and basic computational knowledge.

Qualifications

Required: PhD in genomics, genetics, developmental biology, or other related fields.  Submission of a first-author publication. Experience working with sequencing data and bioinformatic pipelines.

Preferred: First-author publications in regulatory genomics.

To apply:

Required application materials include a cover letter, CV, representative publication, and a code sample. In your cover letter, describe your background, motivation to join our group, and your potential contribution. When you are ready, please submit your application through this portal: Postdoctoral Fellow at Tan Lab. We will review each application carefully and deprioritize applications generated with AI. We will do our best to respond to each applicant but may not be able to if we receive too many requests.

The Tan Lab at NYU is recruiting PhD students to join our effort in developing computational approaches to study gene regulation and its implications for human health. Our research combines machine learning, biological mechanisms, and large-scale data to understand how regulatory elements in our genome control transcription factors, 3D genome organization, and transcription. We are recruiting students who share the same passion for the following research areas:

1. 3D genome organization and transcription factors.

2. Transcriptional regulation and its role in development and disease.

3. Genomic foundation models and synthetic design of biological sequences.

As a PhD student, you will learn how to develop an independent project from 0 to 1. Our work sits at the intersection of machine learning, bioinformatics, and genomics. We understand that few people come in with all the expertise; therefore, we offer opportunities to help you develop and complete your skill set. We aim to train scientists who would thrive in both academia and industry.

How to apply:

1.        Submit a PhD intent form to the lab.

2.        Apply through any of the following programs and refer to me in your application.

List of PhD programs:

1.        The Vilcek PhD Program at NYU School of Medicine

2.        The Data Science PhD program (Medical AI Track) at NYU Center for Data Science

3.        The CS PhD program at NYU Courant

The Tan Lab at NYU accepts MS and undergraduate students to complete their thesis requirements or volunteer as research assistants. Our research combines machine learning, biological mechanisms, and large-scale data to understand how regulatory elements in our genome control transcription factors, 3D genome organization, and transcription. We are recruiting students who share the same passion for the following research areas:

1. 3D genome organization and transcription factors.

2. Transcriptional regulation and its role in development and disease.

3. Genomic foundation models and synthetic design of biological sequences.

As a research assistant, you will work under the supervision of senior lab members and work on a defined project component. Depending on the project, you will learn aspects of machine learning, bioinformatics, and genomics. You will have the opportunity to learn from lab members, develop research skills, and co-author publications.

To apply: Please provide a cover letter, resume, course projects, and your up-to-date transcripts. In your cover letter, describe your background and motivation to join our group. When you are ready, please submit your application through this portal: Research Assistant at Tan Lab. We will review each application carefully and deprioritize applications generated with AI.