We are so proud of our three newly minted Masters graduates from SDSU - Anais, Khuyen, and Michael who successfully defended their theses this week. Congratulations! Watch this space as we post updates and preprints from their research work.
Scott and Ali recently presented their research at the SDSU Student Symposium (S3), where they both gave excellent talks on population genomics of the invasive pink rice borer moth (Sesemia inferens) and hops (Humulus lupulus l.). Scott also won the President's Award for his talk, and advances to present at the California State University-wide competition! Congrats to both!
Gavrila just successfully defended her thesis proposal and has advanced to Masters candidacy! Congratulations and we can't wait to see the awesome Hippodamia convergens genomics work that she will take on as part of her thesis.
Scott and Ian presented their research on estimating heritability and plasticity of body size in Dinocampus coccinellae at the CSUPERB meetings in Santa Clara, CA, while Arun presented research on the D. coccinellae genome at the PAG30 conference in San Diego, CA. Learn more about our research on these topics in our recent publications here and here.
Our lab's new USDA funded project to decipher the genomic evolutionary history of domestication in Humulus lupulus l. (hops) used in beer brewing was featured by SDSU recently. Read more here! Special thanks to Sarah White for the awesome profile and photographs!
Khuyen and Michael successfully defended their thesis proposals and advanced to Masters candidacy recently. Congratulations and best wishes to them on finishing up their theses in the coming term!
Congratulations to Anais Aoki on a splendid Masters thesis proposal defense, which she passed with flying colors and officially advanced to Masters candidacy. We can't wait to hear more about her ongoing research on predictive models for conservation genomics!
The Sethuraman Lab invites applications from potential PhD and Masters students for Fall 2023 - we are looking for scholars with a background and research interest in (1) population genetics/genomics, (2) bioinformatics/computational biology, (3) evolutionary biology, (4) conservation, (5) computer science/applied mathematics, (6) machine learning to join the lab through several graduate programs at San Diego State University:
1) Joint Doctoral Program in Evolutionary Biology (with University of California Riverside)
2) Joint Doctoral Program in Computational Sciences (with University of California Irvine)
1) Masters in Evolutionary Biology
2) Masters in Bioinformatics and Medical Informatics
This recruitment season, we are specifically looking for PhD students interested in the following funded projects:
1) Developing new statistical methods/software for estimating evolutionary history - for examples of methods that we have developed, see: PPP, InRelate, IMa2p, IMGui, MigSelect, and MULTICLUST.
2) Understanding human evolutionary history, specifically in the face of gene flow from archaic ghost populations. We are interested in understanding/estimating signatures of selective sweeps, linked selection, adaptive/maladaptive introgression, load, and demographic history across diverse human populations.
Potential Masters students are welcome to write to me with their broader interests and we can discuss more about potential projects.
Please write to Dr. Sethuraman (email@example.com) with a copy of your CV/Resume, a brief statement of interest, and let’s chat more.
We are committed to recruiting a diverse group of scientists to join my lab group – so we highly encourage folks who identify as a part of historically underrepresented groups to apply. This includes (non-exhaustively) people of color, international students, Veterans of armed forces, student-parents/caregivers, first-generation degree holders, the LGBTQIA+ family, and folks with medical conditions and disabilities.
PI Sethuraman was at the PEQG 2022 meeting in Pacific Grove, CA to present the lab's recent work describing the multinomial clustering method for estimating population genomic structure from polyploid, multi-allelic genomic data. Watch for the preprint describing MULTICLUST! Meanwhile, the tool is accessible via GitHub here.