Active

Single-Cell Genomics and Machine Learning

Department of Genetics and the Department of Computer Science at Stanford University

Dr. Xiaojie Qiu is currently an assistant professor at the Department of Genetics, the BASE program, and the Department of Computer Science at Stanford. Xiaojie’s Ph.D. work at University of Washington with Dr. Cole Trapnell made critical contributions to the field of single-cell genomics, exemplified by the development of Monocle ⅔ (monocle 2 & monocle 3) for pseudotemporal trajectory analysis of scRNA-seq data. In his post-doc at Whitehead Institute and MIT with Dr. Jonathan Weissman, Xiaojie developed Dynamo (https://github.com/aristoteleo/dynamo-release) to reconstruct RNA velocity vector field and make reprogramming and in silico perturbation predictions with metabolic labeling enabled single-cell RNA-seq. Recently he also leaded the development of a powerful toolkit, Spateo (https://github.com/aristoteleo/spateo-release), for advanced multi-dimensional spatiotemporal modeling of high definition spatial transcriptomics.

The Qiu lab at Stanford started on Dec. 16, 2023. Xiaojie will continue leveraging his unique background in single-cell genomics, mathematical modeling, and machine learning to lead a research team that bridges the gap between the “big data” from single-cell and spatial genomics and quantitative/predictive modeling in order to address fundamental questions in mammalian cell fate transitions, especially those of heart evolution, development and disease. His research has been supported by the National Human Genome Research Institute, Chan Zuckerberg Institute, Impetus longevity grant, Arc institute and others.

Main Areas of Interest

Top 5 Areas of Interest for the Fellowship

Single-Cell Foundation Models

Understanding transformer's application in scRNA-seq data.
Application of tabula for genetic perturbation prediction

RNA Velocity and Vector Field Modeling

Use of Dynamo to quantify RNA velocity and reconstruct vector fields of gene expression dynamics.
Exploration of cellular decision-making and fate prediction.

Spatial Transcriptomics

Integration of spatial transcriptomics datasets for tissue-scale gene expression analysis.
Application of Spateo for spatiotemporal modeling and visualization

Machine Learning and Computational Genomics

Training in modern ML frameworks applied to genomic data.
Dimensionality reduction, vector field analysis, and data integration methods.

Specialties

Artificial Intelligence

Bioinformatics

Genetics & Genomics

Biochemistry

Biomedical Engineering

Cell Biology

Techniques You Will Learn

Tabula: Single cell foundation model.

Dynamo: For RNA velocity estimation and vector field analysis.

Spateo: For modeling, analyzing, and visualizing 3D spatiotemporal omics data.

Advanced Data Integration Pipelines: Combining multi-omics (e.g., spatial + scRNA-seq) data using cutting-edge Python-based toolkits developed by the Qiu Lab.

Curriculum

2-12 weeks curriculum can be customized; Here is a sample curriculum and may not necessariliy be followed in your case

6-Week Curriculum Overview

Week 1–2: Foundations of Single-Cell Analysis

Overview of single-cell RNA-seq workflows

Introduction to single-cell foundation models (Tabula)

Exploring transformer-based models in scRNA-seq analysis

Week 3–4: RNA Velocity and Vector Field Modeling

Understanding gene expression kinetics

Applying Dynamo for velocity estimation and dynamic modeling

Cell fate prediction using vector fields

Week 5–6: Spatial Transcriptomics and Data Integration

Introduction to spatial datasets and 3D modeling

Applying Spateo for spatial pattern analysis

Techniques for integrating spatial and single-cell data

12-Week Curriculum Overview

Weeks 1–3: Foundations and Model Applications

Deep dive into Tabula and transformer-based models

Use of pre-trained models in perturbation prediction

Model fine-tuning and validation techniques

Weeks 4–6: RNA Velocity and Dynamics

Theory and practice of RNA velocity

Building and interpreting vector fields with Dynamo

Applications in developmental biology and disease models

Weeks 7–9: Spatial Modeling and 3D Analysis

Spatial transcriptomics principles and platforms

Applying Spateo for spatiotemporal modeling

Visualization and interpretation of tissue-scale dynamics

Weeks 10–12: Multi-Omics Integration and ML Applications

Strategies for integrating scRNA-seq, spatial, and epigenomic data

Using ML for dimensionality reduction and feature selection

Capstone analysis project based on real datasets from the Qiu Lab

Please note that directly contacting the host mentor or their institution regarding the fellowship, housing, visa sponsorship, or any other logistical matters is strictly prohibited.

All inquiries must be directed to Trialect. By applying to this fellowship, you acknowledge and agree to the terms of the Non-Circumvention Agreement, which prohibits any form of direct solicitation or communication with the host mentor or their team outside the Trialect platform.

Violations of this policy may lead to immediate disqualification from the fellowship program and future opportunities on the Trialect platform, but will also be reported to your instituition authorities as a reportable offense.

For all questions, including application process, logistics, fees, or support, please contact:
📩 support@trialect.com

We appreciate your professionalism and cooperation.

Accommodation

You have to take care of your own accommodation and living expenses and travel.

Please note that directly contacting the host mentor or their institution regarding the fellowship, housing, visa sponsorship, or any other logistical matters is strictly prohibited.

Violations of this policy may lead to immediate disqualification from the fellowship program and future opportunities on the Trialect platform.

For all questions, including application process, logistics, fees, or support, please contact:
📩 support@trialect.com

We appreciate your professionalism and cooperation.

Fees and Program Logistics

This program has the following durations available:

Duration	Fee
2 weeks	$1,250.00
6 weeks	$2,250.00
12 weeks	$3,750.00

This program allows Merit Applications. This program allows merit-based applications for virtual and onsite clinical and research programs. If you are successfully awarded under this category, Trialect or the host mentor will cover the tuition fee only. All applications will be evaluated based on merit. Due to the high level of competition, the chances of being selected under the merit category are quite limited.

Who Can Apply

US and EU citizens or permanent residents who do not require a visa for short-term academic visits are eligible to apply.

If needed, an invitation letter will be provided to support your travel documentation.

Please note: The host institution does not offer visa sponsorship. Applicants are responsible for verifying entry requirements based on their citizenship and travel history.

The program is conducted in English, and participants must have a working proficiency in the language.

Priority will be given to candidates who:

Demonstrate alignment with the host lab’s research focus (e.g., single-cell modeling, spatial omics, or ML-driven genomics).
Are affiliated with academic institutions, hospitals, or research organizations.
Can commit to the full duration of the program (6 or 12 weeks).

Trialect reserves the right to screen and approve applicants to ensure alignment with host expectations and institutional requirements.

Host Details

Host Name: Xiaojie Qiu

Affiliation: Department of Genetics and the Department of Computer Science at Stanford University

Address: Stanford University, USA

Website URL: https://www.stanford.edu/

Disclaimer:It is mandatory that all applicants carry workplace liability insurance, e.g., https://www.protrip-world-liability.com (Erasmus students use this package and typically costs around 5 € per month - please check) in addition to health insurance when you join any of the onsite Trialect partnered fellowships.

Legal & Affiliation Disclaimer

Affiliation Disclaimer: Trialect operates independently and is not affiliated with, endorsed by, or supported by any sponsors or organizations posting on the GrantsBoard platform. As an independent aggregator of publicly available funding opportunities, Trialect provides equal access to information for all users without endorsing any specific funding source, content, organization, or sponsor. Trialect assumes no responsibility for the content posted by sponsors or third parties.

Subscription Disclaimer: Upon logging into Trialect, you may choose to SUBSCRIBE to GrantsBoard for timely notifications of funding opportunities and to access exclusive benefits, such as priority alerts, reminders, personalized recommendations, and additional application support. However, users are advised to contact sponsors directly for any questions and are not required to subscribe to engage with funding opportunities.

Content Ownership and Copyright Disclaimer: Trialect respects the intellectual property rights of all organizations and individuals. All content posted on GrantsBoard is provided solely for informational purposes and remains the property of the original owners. Trialect does not claim ownership of, nor does it have any proprietary interest in, content provided by third-party sponsors. Users are encouraged to verify content and ownership directly with the posting sponsor.

Fair Use Disclaimer: The information and content available on GrantsBoard are compiled from publicly accessible sources in alignment with fair use principles under U.S. copyright law. Trialect serves as an aggregator of this content, offering it to users in good faith and with the understanding that it is available for public dissemination. Any organization or individual who believes their intellectual property rights have been violated is encouraged to contact us for prompt resolution.

Third-Party Posting Responsibility Disclaimer: Trialect is a neutral platform that allows third-party sponsors to post funding opportunities for informational purposes only. Sponsors are solely responsible for ensuring that their postings comply with copyright, trademark, and other intellectual property laws. Trialect assumes no liability for any copyright or intellectual property infringements in third-party content and will take appropriate action to address any substantiated claims.

Accuracy and Verification Disclaimer: Trialect makes no warranties regarding the accuracy, completeness, or reliability of the information provided by sponsors. Users are advised to verify the details of any funding opportunity directly with the sponsor before taking action. Trialect cannot be held liable for any discrepancies, omissions, or inaccuracies in third-party postings.

Notice and Takedown Policy: Trialect is committed to upholding copyright law and protecting the rights of intellectual property owners. If you believe that content on GrantsBoard infringes your copyright or intellectual property rights, please contact us with detailed information about the claim. Upon receipt of a valid notice, Trialect will promptly investigate and, where appropriate, remove or disable access to the infringing content.