<p align="JUSTIFY"><strong>Context</strong><strong>.</strong> Understanding how our visual system analyses the trajectory of moving objects is a major challenge in fundamental as well as in applied research with a strong impact in domains such as retina therapy (prostheses) or bio-inspired computer vision.
In the context of the INRIA 2014 recruitment campaign, a PhD position in the field of gene expression modelling is proposed at INRIA Grenoble - Rhône -Alpes (France).
<p style="margin-top: 0px; margin-bottom: 2px; text-align: center; font-size: 12px; font-family: Arial; min-height: 14px;"><b style="letter-spacing: 0px;">Post-doctoral Fellow Opening</b></p><p style="margin-top: 0px; margin-bottom: 2px; text-align: center; font-family: Arial;"><span style="letter-spacing: 0.0px"><b>Novel algorithms for annotating and fitting of electron density</b></span></p><p style="margin-top: 0px; margin-bottom: 2px; text-align: justify; font-size: 9px; font-fami
<h2 style="margin: 0px 0px 10px; padding: 0px; border: 0px; font-family: 'Yanone Kaffeesatz', arial, helvetica, sans-serif; font-size: 30px; line-height: 22px; vertical-align: baseline; color: rgb(34, 34, 34); background-color: rgb(255, 255, 255);">Development of a Novel Exhaustive–Search FFT–Based Method With a Very Detailed Potential for Protein Docking</h2><p style="margin-top: 0px; margin-bottom: 25px; padding: 0px; border: 0px; font-family: sans-serif; font-size: 14px; line-height: 22px; vertical-align: baseline; color: rgb(51
IRISA & INRIA Rennes
Campus de Beaulieu
35042 Rennes cedex
Dyliss is a research team in bioinformatics. We focus on sequence analysis and systems biology. We use qualitative formal systems to characterize genetic actors from non model species, such as algae or mining baceria, that control phenotypic answers when challenged by their environment.
- Methods: constraint logic programming, symbolic dynamics, machine learning, formal systems.
- Expertise: functional characterization, non-model species, multi-scale integration.
- Application domains: marine biology, micro-environmental biology...
The main computational challenge is to face lacks and incompleteness in both expert knowledge and experimental observations. Our strategy relies on three main points.
- We focus on a targeted functional characterization rather than on a complete understanding of the species.
- We rely on knowledge rather than on amounts of experimentations.
- We use model-species to validate methods.
We use qualitative formal systems for knowledge acquisition and integration. All our methods aim at identifying the space of all models that are consistent with both knowledge and observations. Then we provide tools to navigate in this space in order to investigate which properties are shared by a large proportion of the space.
06902 Sophia Antipolis
GenScale is a bioinformatics research team. Its main goal is to develop scalable methods, tools, and software forprocessing genomic data.
Our research is motivated by the fast development of next-generation sequencing (NGS) and third generation (TGS) technologies that provide very challenging problems both in terms of bioinformatics and computer sciences.
GenScale research is organized along four main axes:
- Data structures
- Indexing the mass of genomic data
- Focus on the de-Bruijn graph structure.
- Provide end-user and optimized library
- Optimized (time and memory) tools dedicated to NGS processing
- Data compression, genome assembly, variant detection, metagenomics, GWAS (genome-wide association Study)
- Combine several levels of parallelism
- Use existing techniques as multithreading or MapReduce
- Constrained algorithmic development, in particular, targeting hardware accelerators
- Participate in biology-oriented projects
- Inra, CEA, National Museum, Hospitals, …