Now hiring a computational postdoc (evolutionary genomics, molecular evolution) in my lab at Emory University.
If you’re interested in population genetics, fitness landscapes, and viral evolution — get in touch.
faculty-emory.icims.com/jobs/151181/...

So excited for you and your group! Congrats!

Staff scientist position (computational):

I am looking for a computational scientist to join my genomics lab at Stanford. They should have an outstanding skillset in ML/statistical methods for genomic applications, postdoc experience and a strong publication record.
#sciencejobs

Unfortunately not, but happy to chat offline!

Looking forward to #evolution2025! I will be talking about how time-varying demography and selection shape the site frequency spectrum — Saturday at 4:15 pm, Population Genetics Theory IV. Come say hi if you are around!

I'm excited to announce that I'll be starting a lab at UCSF in the @ihgatucsf.bsky.social and @ucsf-epibiostat.bsky.social in July.

We'll work at the intersection of statistical genetics, population genetics, and machine learning.

Letter signed by members of the Columbia History Department urging resistance to the Trump Administration's efforts to dictate university policy.

"Should this control be realized, here or elsewhere, it would make any real historical scholarship, teaching, and intellectual community impossible."

Here we show that within-cell competition is key to plasmid evolution. Look at this photo of plasmids competing inside cells in a colony!!!

We are excited to announce a new faculty position here in Cambridge, for researchers in computational and/or theoretical biology, based jointly in Genetics and Mathematics. Come and join us! Happy to answer questions about research, teaching and working here. www.jobs.cam.ac.uk/job/50414/

This allowed us to visualize the pattern of clones in the tumor! 10/16

Project scientist in computational population genetics (post PhD/postdoc experience usually expected). recruit.apo.ucla.edu/JPF10171

Happy to have been part of this story!

This paper has been a long time coming: We looked at the genomes of historical bacterial samples over a century to look for trends of antibiotic resistance genes, finding multiple instances of them in infections before the age of antibiotics, but an increase in both frequency and mobility after

For many traits there is a correlation between the number of duplications or loss-of-function (LoF) mutations someone carries, and their phenotype. Curiously, for most traits, these effects are aligned in the SAME direction. Why?

I am glad to see this work in print & on the cover! Read more at academic.oup.com/genetics/article/228/3/iyae145/7747749

Moving forward, we hope that our theoretical framework can be a starting point for understanding frequency-resolved linkage more broadly. We would love to hear your thoughts!

Our analytical results lead to several empirically relevant findings, e.g. that the dependence of homoplasy on the frequencies of the alleles can distinguish the effects of recombination from the confounding effects of recurrent mutation and epistasis.

We derive how these homoplasy measures depend on the rates of recombination and recurrent mutation, the strength of negative selection and genetic drift, and the present-day frequencies of the mutant alleles.

In this work, we analyze an alternative class of two-locus statistics that quantify the homoplasy produced by recombination. These measures vanish in the absence of recombination and recurrent mutation and approach one in the limit of linkage equilibrium.

Interpreting these decay curves is notoriously difficult since the magnitude of these correlations is shaped by phenomena like epistasis and demography in addition to recombination (e.g. from @nanditagarud.bsky.social et al. – can recombination be behind the fast decay at short distances?).

While a large body of population genetics theory has been devoted to this topic, much of our existing understanding has focused on pairwise correlations, and how they decay with the distance between loci.

How do we predict the statistical associations between mutations that spontaneously emerge in an evolving population? Excited to share some new work w/ @zzzhiru.bsky.social and @benjaminhgood.bsky.social that approaches this question!

I’m excited for my first preprint in the Good lab, a theory project predicting the first steps of evolution in microbial communities with resource competition. If you’re interested in how community context shapes the availability and impact of mutations, read on!

doi.org/10.1101/2023.12.15.571925