NEXTIMMUNE, standing for Next GenerationImmunoScience : Advanced Concepts for Deciphering Acute and ChronicInflammation , is a competitive PhD training program , supported by the doctoral research funding scheme PRIDE of the LuxembourgNational Research Fund FNR.
It aims to bridge classical immunology and big-dataanalysis science in a structured doctoral training environment. NEXTIMMUNE is opening.
with up to 4 years fixed-term contract, full-time . Start dateflexible from now on until July 2018. Supervisor : Prof. Jorge Goncalves,Systems Control Group at the Luxembourg Centre for Systems Biomedicine (LCSB)of the University of Luxembourg.
The research-intensive program aims torespond to the unmet need of training the next generation of competentimmunologists by tackling next generation immunology challenges from wet labprocedures to big data analyses.
We offer an interdisciplinary environment thatcovers analysis of omics and clinical data, as well as basic andtranslational biomedical knowledge combined with its practical application todiagnosis and ultimately therapy.
The program includes transferable skillstraining, support in career development, scientific lectures by internationalspeakers and annual PhD retreats.
A main research interest within the Systems Control Group at the University of Luxembourg is network inference, which means to address the inverse problem consisting in inferring from time-
series data the topology and properties of the underlying network which generated the data.Within the scope of the NextImmune Doctoral Training Unit, following the dynamic measurements in different patients, Jorge Goncalves’s group will use established computational tools adapted from the field of control engineering to identify potential regulatory causality between genes in Th2 cells, the major adaptive immune cells of allergic inflammation.
This will provide a directed network of cause-effect relationship between measurements (genes). Strong mathematical background is a requirement.
Hence, the student must hold a mathematics, engineering or physics degree. If not already covered in their background, students must also learn advanced mathematic courses from the mathematics department including analysis, functional analysis and linear algebra.
Biological knowledge is not essential.
Candidate profile :
Applications including a motivation letter describing past research experience and future interests, at least two confidential references letters, a full curriculum vitae and a copy of the relevant diplomas showing marks should be sent via the apply button below.
Only complete applications will be considered.