-
apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and
-
a plus. Be technically rigorous, curious and creative. Show enthusiasm in tackling complex biological problems and developing/applying new technologies. Have advanced at least one key research project
-
RNA-seq, single-cell ATAC-seq, multiome, etc). Demonstrated ability to effectively communicate about complex bioinformatics problems to both technical and non-technical audiences. Independent, highly
-
characterization of membrane protein complexes that mediate inflammatory signaling by using a confluence of structural, biochemical, cell biological and computational tools. The candidate is expected to work
-
genomics and transcriptomics, single-cell RNA-seq, Perturb-seq) Demonstrated ability to clearly and effectively communicate about complex bioinformatics problems to both technical and non-technical audiences
-
field ● Demonstrated proficiency with R or Python Preferred ● Demonstrated ability to effectively communicate about complex bioinformatics problems to both technical and non-technical audiences
-
chemical and genetic perturbation tools coupled with high content imaging and single cell -omics to screen for regulators of disease states in complex in vitro human models Decode biological insights from
-
. -Technical Expertise: Proficient in advanced cellular and molecular techniques, you are eager to leverage state-of-the-art genomic and transcriptomic technologies to address complex questions in immune cell
-
communicate about complex genetic and statistical questions to both technical and non-technical audiences Preferred: Independent, highly motivated, and highly collaborative with the ability to work together