Ryan Hernandez

Looking for a start in science? National PROPEL will host faculty looking to hire full-time research technicians from 5 institutions on Jan 30th. Meet faculty with similar research interests in a series of 10 min interviews. More info at propelscholars.org/matchmaking-event

Building a community of PROPEL-affiliated programs at UCSF, U. Utah, UCSC, MUSC, U. Iowa, UW/Fred Hutch, OHSU, and Stanford!

There are unprecedented challenges for science, calling for bold action and collective effort. Training the next generation of scientific leaders has never been more important. Join us as we grow National PROPEL to answer this call. Learn more: propelscholars.org @propelscholars.bsky.social 🧪🧬🖥️🧵

Robust and accurate Bayesian inference of genome-wide genealogies for hundreds of genomes - Nature Genetics SINGER is a method for creating ancestral recombination graphs to understand the genealogical history of genomes. The method has increased speed, and thus scalability, without sacrificing accuracy.

SINGER, our ARG inference method, is finally published and freely available online:

doi.org/10.1038/s415...

It was a long journey – 16 months from initial submission to acceptance. Is it just me, or has peer review gotten more arduous lately? 4+ rounds of review isn't so unusual these days...

I want to try something again at #ASHG25 this year: I'll block some time on Thursday and Friday afternoons to meet with trainees who would be interested to chat on any topic.

I did this last year and it was great to meet a whole bunch of new people, at all career stages!

Inference of complex demographic history using composite likelihood based on whole-genome genealogies Accurate parametric inference on complex demographic models is a continuing challenge in population genetics. Ancestral recombination graphs (ARGs) provide richer information than simple population ge...

Excited to preprint our latest work (w/ Drew DeHaas, Zhibai Jia, Leo Speidel) on using ARGs for demographic inference. w/ applications using data from 1000 Genomes Project. www.biorxiv.org/content/10.1...

🌟 Together, we can open equitable routes into science and build a future where talent—not privilege—drives breakthroughs. Your participation can change a trajectory. Scholars, PIs: Join us for National PROPEL’s Matchmaking Event and be part of this transformation. Learn more: propelscholars.org 🙌

📅 Key dates:
🧑‍🔬 Info session for scholars: Nov 14, 9–10am PT
👩‍🏫 Info session for faculty: Nov 14, 10–11am PT
📝 Register by: Dec 5
🖥️ Event: Jan 30, 2026 (virtual)
🔗 Register: propelscholars.org/matchmaking-...

How it works: Scholars and faculty share interests, meet in structured 10-minute conversations, then follow up for formal interviews and hiring. 🧬 National PROPEL creates connections to open paid pathways into science. Learn more: propelscholars.org

But PhD readiness goes beyond research—it’s about building scientific identity, scientific self-efficacy, leadership skills, and the confidence to thrive in grad school and beyond. Scholars receive mentoring and holistic support to help them succeed.

What scholars receive: livable salary, research training, professional development, and academic enrichment. These opportunities prepare scholars for meaningful careers in science while supporting their journey toward their PhD.

But there’s a debate: Do paid postbac programs measurably improve PhD readiness and scientific leadership? We’re committed to assessing outcomes—not just anecdotes. With the Center for Evaluation & Assessment (U Iowa), we’re collecting and analyzing data to inform the future of graduate education.

Why this event? National PROPEL is testing a hypothesis: increasing paid postbac research opportunities will increase PhD readiness, broaden the talent pool in graduate education, and prepare scholars to become the next generation of scientific leaders. 🧪💡🌟

Paid postbac pathways can help remove barriers that shut out talented students. National PROPEL is building equitable opportunities for research experience to widen the talent pool—and strengthen the future of science. 🌟 Learn more: propelscholars.org

That’s why National PROPEL is facilitating connections through its Matchmaking Event, where you can meet faculty ready to hire you! Apply by Dec 5. Scholar info session Nov 14, 9–10am PT: propelscholars.org/matchmaking-...

Scholars: Are you a senior or recent grad thinking about a PhD? Sustained research (~2+ years) builds PhD readiness, but many lack access to paid research or discover opportunities too late—barriers that shut out talent.

PIs at UCSF, OHSU, U Iowa, UW–Madison, and VCU: Want to hire/train postbac scholars in pursuit of a PhD? Meet talented trainees through short 10‑minute virtual interviews during our Matchmaking Event! Register by Dec 5. Info session Nov 14, 10–11am PT. Details: propelscholars.org/matchmaking-...

Growth of UCSF PROPEL. Since 2021, over 200 scholars have been hired at UCSF!

Since 2021, >200 postbac scholars have joined UCSF PROPEL, and 83% of those applying to PhD programs got in! Scholars want opportunity. PIs want to train. The demand is clear—so we’re scaling nationally! Join our 2026 Matchmaking Event to connect PIs & scholars in CA/OR/IA/WI/VA: propelscholars.org

Building a community of PROPEL-affiliated programs at UCSF, U. Utah, UCSC, MUSC, U. Iowa, UW/Fred Hutch, OHSU, and Stanford!

There are unprecedented challenges for science, calling for bold action and collective effort. Training the next generation of scientific leaders has never been more important. Join us as we grow National PROPEL to answer this call. Learn more: propelscholars.org @propelscholars.bsky.social 🧪🧬🖥️🧵

Estimating the rate of quantitative trait evolution in the presence of gene tree discordance by calculating likelihoods across trees https://www.biorxiv.org/content/10.1101/2025.10.06.680724v1

Interpreting supervised machine learning inferences in population genomics using haplotype matrix permutations Abstract. Supervised machine learning methods, such as convolutional neural networks (CNNs), that use haplotype matrices as input data have become powerful

Working link: academic.oup.com/mbe/advance-...

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We developed a systematic permutation approach that progressively scrambles features (LD, haplotype structure, allele frequencies) in haplotype matrices to see how each affects model performance.

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Excited to share our new paper in Molecular Biology & Evolution!
👉 [https://doi.org/10.1093/molbev/msaf250]
It started as a lab-meeting sanity check for another project — and ended up turning into a new way to interpret machine-learning models in population genomics.

Yes, the rice… would have been better than what I tried: sticking it over an air purifier… #didnotwork

Sadly, it did not take well to this… 🤬😥

🪦💀💔

Nooooo!!! Guess I didn’t completely close my water bottle in my backpack… good thing I have 27 minutes until my lecture begins to find a solution…. 😱

This is truly an incredible breakthrough IMO. Really exemplifies what you get when deep domain expertise (popgen/evolution/disease genetics in this case) fuses with cleverly crafted ML. What u get r sleek, well thought out architectures that absolutely destroy the behemoths. Wow!! 1/

We are excited to share GPN-Star, a cost-effective, biologically grounded genomic language modeling framework that achieves state-of-the-art performance across a wide range of variant effect prediction tasks relevant to human genetics.
www.biorxiv.org/content/10.1...
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WONDERFUL!!!