Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
their ontogeny and developmental trajectories (https://www.nature.com/articles/s41586-026-10198-z ). The lab’s work transitions between mechanistic studies in experimental models and translational human immunology
-
Pytorch and/or JAX deep learning models. Experience in single-cell or spatial omics data analysis. What we offer Embedding within a computational team, with extensive experience in computational biology and
-
Pytorch and/or JAX deep learning models. Experience in single-cell or spatial omics data analysis. What we offer Embedding within a computational team, with extensive experience in computational biology and
-
, or agricultural greenhouse gas estimation. Proficiency in working with spatial data and geospatial tools. Interest in science–policy interfaces. What you will do Develop and apply biophysical and economic models
-
colleagues from FBMH. Areas of current research are novel dose delivery methods (FLASH therapy and spatially fractionated), imaging (using prompt photons and proton CT), high throughput radiobiology
-
staff. We conduct research in several areas: analysis of high-dimensional data, Bayesian methods, spatial-temporal models, non-Gaussian modeling, applied research in social science, as well as stochastic
-
have: Ph.D. in Biostatistics, Statistics, Bioinformatics, Data Science, or related field; with (i). technical skills such as Proficiency in R, Python, or SAS for statistical analysis and modelling; (ii
-
Neuroscience, or a related field—or an equivalent combination of education and relevant experience. 3+ years of experience fine-tuning spatial transformer networks, contrastive learning, model distillation, RLHF
-
BIOS-06/A - A synaptic mechanogenetic technology to repair brain connectivity - CUP: J93C22002400006
of neural networks. The technology will be validated in mouse models of neurological disorders. Where to apply Website https://pica.cineca.it/units Requirements Additional Information Eligibility criteria
-
conditions. However, current global climate models (GCMs) lack the spatial resolution to capture these processes, while high-resolution regional models remain too computationally expensive for large ensemble