Tinyi Chu

Assistant Professor, University of Virginia | @NIH K99/R00 Fellow

[Tinyi Chu @tinyichu]

correction: please use [email protected]

[Tinyi Chu @tinyichu]

Hiring postdocs in my new lab @ UVA — computational biology + ML.

The Mission: We develop modern machine learning, including generative modeling, physics-informed neural networks and neural differential equation, to decode single-cell, spatial and liquid biopsy data. Our goal is to uncover the complex cellular and tissue dynamics underlying cancer, inflammation, and tissue senescence.

Our Philosophy: Mentorship as Collaboration 🤝 In our lab, trainees are collaborators, not assistants. You can expect direct technical engagement in algorithm development, genuine intellectual exchange, and co-ownership of the science. The PI is deeply committed to providing hands-on training in grant writing and supporting your path to an independent career.

Who We Are Looking For: 🔹 Ph.D. in Computer Science, Applied Math, Statistics, Physics, Computational Biology or a related quantitative field. 🔹 Proficiency in PyTorch (or equivalent deep learning frameworks). 🔹 Biological background is a plus, but NOT required! We strongly encourage candidates from purely computational backgrounds to apply—domain-specific biology can be acquired on the job.

What We Offer: ✨ Fully funded positions backed by an NIH R00 Award and substantial UVA startup funds. ✨ Rich GPU/HPC computing infrastructure. ✨ A vibrant, highly collaborative environment in beautiful Charlottesville, VA.

If you are passionate about building the next generation of AI tools for spatial and single-cell biology, let’s connect!

📩 How to Apply: Send your CV and a brief cover letter to [email protected]
🌐 Full Job Description & Lab Vision: https://t.co/RWZZAxj9Sl

Please feel free to share or tag anyone in your network who might be a great fit!

#postdoc #compbio #MachineLearning #singlecell #genomics #academicjobs

[Tinyi Chu @tinyichu]

Grateful to @NCIHTAN #HTAN for featuring my work! Excited to announce that the next version of BayesPrism is coming soon—stay tuned!

[Tinyi Chu @tinyichu]

Beautiful work. Congratulations to @GaoVianne and @RuiYang53922541

[Rui Yang @RuiYang53922541]

Out in @NatureComms ! ChromaFold predicts 3D contact maps using single-cell ATAC-seq alone. https://t.co/54MIrOSwCr

[Tinyi Chu @tinyichu]

@liuqiao_ Thank you so much, Qiao.

[Tinyi Chu @tinyichu]

I’m excited to share part of the computational analysis where we combined BayesPrism and Hotspot to prioritize cell-type-specific spatially variable genes and gene expression modules.

[Rodrigo Romero Rangel @RRomero_PhD]

🚨🚨Now online @NatureCancer, my postdoc work in @SawyersLabMSKCC with @dana_peer 🚨🚨 we establish a powerful organoid transplantation model of prostate cancer neuroendocrine transformation. Open access for all! @HHMINEWS
https://t.co/FJc0WSBvDQ
A 🧵... /1

[Tinyi Chu @tinyichu]

@RongFan8 Thank you so much, Rong.

[Tinyi Chu @tinyichu]

@Yubin_Xie and @RRomero_PhD furthered the spatial biology analysis of rare immune cell types through a powerful 20-marker COMET-based multiplexed immunofluorescence. Check out our paper in https://t.co/bS6PjiAY8i!

[Tinyi Chu @tinyichu]

Notably, the top spatially variable gene, Ascl1, emerged as the driver transcription factor of the NEPC phenotype, highlighting the potential of spatially variable gene identification in prioritizing genes driving lineage plasticity and tumor heterogeneity.

[Tinyi Chu @tinyichu]

Kudos to @RRomero_PhD for publishing fascinating work on the lineage plasticity of prostate cancer. It’s been an incredible learning experience with @RRomero_PhD , @CharlesSawyers and @dana_peer.

[Rodrigo Romero Rangel @RRomero_PhD]

🚨🚨Now online @NatureCancer, my postdoc work in @SawyersLabMSKCC with @dana_peer 🚨🚨 we establish a powerful organoid transplantation model of prostate cancer neuroendocrine transformation. Open access for all! @HHMINEWS
https://t.co/FJc0WSBvDQ
A 🧵... /1

[Tinyi Chu @tinyichu]

@_tom_dot_com @dana_peer @AACR @ciacobu Hi Tom. Thank you for your interest in this tool. I am hoping to wrap it up and release it as an R package soon. Will keep you posted.

[Tinyi Chu @tinyichu]

Thrilled by @dana_peer talk at @AACR ! My algorithm, scClock (Single Cell Clonal Lineage Of Copy Number Kinetics), showed its prowess in reconstructing clonal trees using snRNA-seq and WES of rapid autopsy from PDAC patients (in collaboration with Chris Iacobuzio @ciacobu)#AACR24

[Tinyi Chu @tinyichu]

@dana_peer @AACR @ciacobu @MSKCancerCenter

[Tinyi Chu @tinyichu]

@digvijayky @ICCVConference Huge congratulations, Vijay!

[Tinyi Chu @tinyichu]

Thrilled to attend my first and final in-person Damon Runyon Retreat during my postdoc training. It was a joy to connect with fellow researchers and staff. A heartfelt thank you to the @DamonRunyon Foundation for their unwavering support throughout my journey #damonrunyonretreat

[Tinyi Chu @tinyichu]

@DigbijayMahat Looking forward to looking into the data!

[Tinyi Chu @tinyichu]

@Yubin_Xie Thank you, Yubin!

[Tinyi Chu @tinyichu]

Delighted to share that BayesPrism consistently ranks as the top-performing deconvolution approach in another independent benchmark studies. 🌟

If you or someone you know can benefit from my work, feel free to share this link:
https://t.co/QXUmlXLEsL

[Charles Danko @charlesdanko]

Another independent benchmark of deconvolution tools ranks BayesPrism as the top performing. Gratifying to see the many years @tinyichu spent developing BayesPrism paying off!
https://t.co/I068udJtbS

[Tinyi Chu @tinyichu]

Huge congratulations to Jay Mahat @DigbijayMahat and other members of the Sharp lab. This is the breakthrough method I've been anticipating since my time at Danko lab. 🌟

[Charles Danko @charlesdanko]

Great to finally see a single cell GRO-seq assay! Hoping we can buy the clickable rNTPs soon.

Congratulations on this extremely creative approach to Jay Mahat and other members of the Sharp lab.
https://t.co/3LrU7AcM3D

[Tinyi Chu @tinyichu]

@charlesdanko @NatureGenet Huge congratulations to Charles, Gilad and co-authors!