12 parallel-computing-"https:"-"INL---INSA-Lyon" positions at Centre for Genomic Regulation in Spain
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
computational, and we do both large-scale data analysis and development of methods, but it has also an important experimental component. We participate in many large scale international functional genomics
-
26 Feb 2026 Job Information Organisation/Company Centre for Genomic Regulation Research Field Computer science » Other Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions
-
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Institute The Centre for Genomic Regulation (CRG) is an international
-
using a combination of single cell genomics, genetic screens, and computational biology. We strive to develop novel genomic and bioinformatic tools to answer longstanding questions in the field. We cover
-
31.8.2027) Job Status Full-time Hours Per Week 38.5 Offer Starting Date 15 May 2026 Is the job funded through the EU Research Framework Programme? Other EU programme Reference Number PID2023-146699NB-I00 Is
-
the Institute of Mountain Genomics, a joint research initiative that combines Andorra’s high-mountain ecosystems with CRG’s expertise in genomics, computational biology and biotechnology. The initiative is
-
. We combine molecular biology, imaging, genomics, and computational approaches to address fundamental questions in genome regulation. The lab fosters a collaborative and interdisciplinary environment
-
these questions, we develop mathematical and computational approaches to estimate mutation probabilities and selection. Tumor mutations are caused by diverse mutational processes, which can be identified through
-
effects) and metagenomics (microbiome profiling using deep shotgun sequencing data, detecting horizontal transmission). We are mostly computational but have a small lab component and work in close
-
). The candidate will design and apply integrative data analysis (computational/statistical/causal) and visualization techniques for multi-omic (transcriptomics, mirnomic and proteomics) data to address research