Dr. Armita Nourmohammad
@TheArmita
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physicist, interested in biology --- Assoc. Prof. of physics @UW (Seattle)
Joined July 2016
#TheoBiophysicsPosition .We are recruiting postdocs at @UW (Seattle)! Join us if interested in bridging Stat. Phys. with immunology, proteins & evolution. Our work is theoretical & computational with experimental collaborations. info: . Some recent work:
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this work was initiated by Mike Pun (now at @vant_ai), and is built on his work on H-CNN: fantastic collaboration with @Asya_Minervina @PGTimmune , and Phil Bradley.
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check out our new manuscript (led by @GMarcoVisani). structure-based machine learning model for TCR-pMHC complexes, predicting T-cell affinity to peptide-MHC complexes, quantifying T-cell receptor specificity, and designing de-novo immunogenic peptides: .
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RT @giulioisacchini: Curious about generative modeling for T and B cell receptor repertoires and its role in understanding immune system di….
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RT @ohallats: 🚨 Job Alert! 🚨 Join the UC Berkeley Physics Department! We’re hiring an Assistant Professor in soft condensed matter (broadly….
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RT @SettyM: Are you an early career scientist who wants to pursue a research project in the lab of a Fred Hutch Computational Biologist men….
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RT @BiologyAIDaily: HERMES: Holographic Equivariant neuRal network model for Mutational Effect and Stability prediction. 1. HERMES introduc….
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RT @ApsDbio: Are you an undergraduate interested in pursuing graduate studies biological physics? Join us for a virtual panel “Applying to….
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RT @fepinheiromycin: My 'Predicting the evolution of antibiotic resistance' is out now 🤓🥹. I review a topic that's….
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RT @p_r_francois: We are hiring post-docs! Please do not hesitate to share. We are especially looking for candidates with strong theory a….
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Check out HERMES, our equivariant structure-based suit of models to predict stability and fitness effect of mutations, led by @GMarcoVisani. bonus: fine-tune your own protein models. Google Colab:. Github:.
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RT @rahmstorf: We don’t want this climate future for Europe - in my view it’s a risk we should avoid at all cost, as I explain in this vide….
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RT @rahmstorf: Is the #AMOC approaching a tipping point? Here's my take after researching this topic for over 30 years. Open access, peer-r….
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RT @TLM_Cambridge: 🚨Wed 29/05 - @TLM_Cambridge online seminar🚨 .Professor Hernan García @HernanGGarcia (UC Berkeley) on “Using Physics as a….
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RT @NITMB_Chicago: Do you have an excellent idea for an NITMB Long Program?. Learn how the NITMB can support you as you develop your idea i….
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very excited about the upcoming theory of living matter seminar @TLM_Cambridge.
🚨 @TLM_Cambridge Wed 22/05 | 16:00 UK - Online Seminar 🚨. "Learning the shape of the immune and protein universe" by Armita Nourmohammad @TheArmita. Please RT & to attend online please register to our 📧:
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RT @ChrisWLynn: For postdocs and other early-career physicists, this is a great way to get involved!.
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RT @sara_mostafavi: Joins us for Machine Learning in Computational Biology (MLCB) 2024 Submission deadline: June 1….
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RT @ChavarriaAlvaro: Dr. John C. Mather from @NASA will give the next Frontiers of Physics Public Lecture at @UW Seattle on May 8th. Regist….
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RT @PhysRevResearch: Holographic-(V)AE: An end-to-end SO(3)-equivariant (variational) autoencoder in Fourier space, Gian Marco Visani, Mich….
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check out our new work led by @GMarcoVisani.on equivariant holographic variational auto-encoder (H-VAE) in @PhysRevResearch. it extracts geometry-aware compressed representations of 3D point clouds, e.g. proteins, used for protein binding prediction &.
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