We are looking for self-motivated, passionate researchers, both dry (machine learning, computational biology) and wet (single-cell and spatial genomics), to help dissect the molecular mechanisms behind evolution, development and disease.
We are a multidisciplinary team of biologists, computer scientists, engineers, mathematicians and physicists, and we offer a collaborative training environment where students, postdocs, RAs, staff scientists and visitors grow into future leaders in academia and industry.
| Position | Status | Background we look for |
|---|---|---|
| Postdoctoral Fellow | Actively recruiting | AI/ML, computational biology, genomics |
| Research Assistant | Actively recruiting | Computational or experimental |
| Staff Scientist | Actively recruiting | AI, genomics, developmental biology |
| Graduate Student | Open to Stanford students | Genetics, CS, Bioengineering, BMDS, Biophysics and others |
| Visiting Researcher | Limited availability | Subject to Stanford policy and a one-year minimum |
Virtual embryos
Predictive, whole-embryo models of mammalian development and congenital disease.
Foundation models
Single-cell and spatial foundation models, from tabular pretraining to federated learning.
Perturbation modeling
Predicting how cells respond to genetic and environmental perturbation, and why.
Generative AI for genomics
Flow and diffusion models, neural ODEs and multimodal generative methods.
AI-native platforms
Agentic systems for biology, such as PantheonOS and Bio-Babel.
Spatial genomics
Metabolic-labeling scRNA-seq, ultra-high-resolution spatial transcriptomics and lineage tracing.
See the research page for how these fit together, and papers for recent work.
Who we're looking for
Graduate Students
Graduate students from any Stanford department are warmly encouraged to contact Dr. Qiu directly. We frequently hear from students in Genetics, Bioengineering, Computer Science, Biomedical Data Science and Biophysics.
Undergraduate Students
Stanford undergraduates interested in research and honors theses are welcome to reach out. Many gain the research experience and mentorship that helps them apply successfully to top-tier PhD programs.
Visiting Students
We welcome highly motivated visiting undergraduate, Master's and PhD students. Interest is high, so selection is competitive and must comply with Stanford policy and U.S. visa regulations. Please see the Stanford requirements for UGVI and VSR visitors.
- Undergraduate and Master's visitors: Stanford policy permits short stays only, such as a summer visit. This is a university restriction, not a lab preference.
- Visiting PhD students: at least one year, and preferably longer. J-1 policy allows stays of up to 2 years.
- Long-term visiting students receive full salary support.
We invest substantially in every visiting student, with full salary support and close mentorship, and we set a correspondingly high bar in return.
- Commit to at least one year, and preferably longer. Our most successful visiting students have stayed two years or more.
- Expect to do real science. Two visiting students currently in the lab have each published or submitted multiple papers, to journals including Cell, Nature Protocols and Nature Methods.
- Short visits rarely work. Most projects simply do not have enough time to develop into scientifically meaningful outcomes in a few months. We have made one exception, for a student who arrived with a project already underway and worked with exceptional independence.
- A Stanford line on a CV is not a reason to apply. Given the time and resources we commit to each visitor, we cannot accommodate short-term visits intended mainly to add a Stanford visiting experience.
We say this not because publications are what matter, but because they reflect the commitment a scientifically meaningful visit requires. If you are weighing what arrangement might work, write to Dr. Qiu and we can discuss it.
Our alumni have gone on to Stanford, Yale, Columbia and USC. See the alumni from the people page.
Research Assistants, Postdocs & Staff Scientists
We are actively hiring research assistants, postdoctoral fellows and staff scientists. Applications are reviewed on a rolling basis.
Where our lab members have gone
A few of our former students, visiting researchers and staff, and where they went next.
See the full alumni list on the people page.
How to apply
Email the following to Dr. Qiu at xiaojie@stanford.edu:
- Your CV, including prior research experience
- A GitHub link, for computational candidates
- A short cover letter describing your motivation and career goals
- Contact details for three references
What you can expect from us
- Interdisciplinary training across AI, single-cell genomics, spatial genomics and developmental biology
- Collaborations across Stanford Genetics, Computer Science, Bioengineering and other departments
- A role in the Virtual Embryo Platform and international challenges, including the NeurIPS 2026 Virtual Embryo Challenge
- Strong placement outcomes for students and visiting researchers, as shown below
- High-impact publications and widely used open-source tools such as Dynamo, Spateo, Tabula, PantheonOS and Bio-Babel
- Personalized mentorship, and coaching in scientific storytelling from writing to presentation
- Tailored career support for academia, biotechnology and entrepreneurship
What we look for in you
This applies to postdocs, graduate students, research assistants and staff scientists alike. Technical skill matters, but it is rarely what decides a fit.
- Intellectual fit. Genuine excitement about the questions this lab is asking. The best work here comes from people who would want to think about these problems anyway.
- Integrity. Honesty in your data, your analyses and your credit to others, and candor when something is not working. We hold ourselves to this and expect the same in return.
- Innovation. A willingness to take on hard, uncharted problems rather than incremental ones, and to keep going when the first several approaches fail.
- Follow-through. Projects carried to completion, including the unglamorous last stretch of revisions, rebuttals and submission. Collaborators and co-authors depend on it, and finishing well is what turns effort into science that counts.
- Collegiality. Sharing what you learn, supporting the people around you, and raising concerns directly and early so they can actually be addressed.