Sort by
Refine Your Search
-
Category
-
Field
-
-career scientist to develop cutting-edge machine learning approaches for understanding and designing pathogen antigens. This is a unique opportunity to help shape a new research program at the intersection
-
computational workflows and high-performance computing Experience handling large population-genetic simulations (e.g., SLiM, msprime, tskit) Application: Interested applicants should email Aimee Taylor (ataylor
-
development. We design, fabricate, and validate microphysiological systems that recapitulate human tissue and organ physiology with high fidelity. Our work sits at the interface of bioengineering
-
framework (Simulation Open Framework Architecture) High-performance computing and cluster computing experience Background in biomechanics, robotics, or computational neuroscience Additional Assets: Experience
-
severity, encompassing clinical and body weight evolution, survival, viraemia, and immune profile, and genotyped using high-density SNP arrays. Genotype-phenotype association studies will then be conducted
-
the interface of machine learning and biology, developing innovative machine learning methods for single-cell data analysis (tools developed by the team: https://github.com/cantinilab). Single-cell high
-
physiological function of cellular senescence, and how does it transition from a regenerative program to a driver of pathology? We investigate how senescent cells control tissue plasticity and microenvironmental
-
we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. All information these cookies collect
-
biological systems such as ecological and neural dynamics. The project is particularly suited to a student with a strong background in physics, applied mathematics or theoretical/computational biology who is
-
PRDX6-PLA2 block intraerythrocytic blood stage growth. This collaborative project with Université de Lille and Institut Pasteur de Lille will develop and use high throughput assays to identify novel