PhD Student in Computational Immunology - Nextimmune DTU - LCSB JG

NEXTIMMUNE, standing for “Next Generation ImmunoScience: Advanced Concepts for Deciphering Acute and Chronic Inflammation”, is a competitive  PhD training program, supported by the doctoral research funding scheme PRIDE of the Luxembourg National Research Fund FNR. It aims to bridge classical immunology and big-data analysis science in a structured doctoral training environment. NEXTIMMUNE is opening.

One Phd Position is available in the Systems Control Group of the University of Luxembourg, in the framework of the NextImmune Doctoral Training. The PhD project will focus on “prediction of causal regulatory interaction networks based on large-scale time-series data”.

Fixed-term contract 14 months, renewable depending on thesis progress evaluation (Project funding available for up to 48 months with a competitive salary).
Full-time (40h/p.w.)
Start date : ASAP and before July 2019.
Student and employee status
Supervisor: Prof. Jorge Goncalves, Systems Control Group at the Luxembourg Centre for Systems Biomedicine (LCSB) of the University of Luxembourg.

YOUR ROLE

Project description:

“Prediction of causal regulatory interaction networks based on large-scale time-series data”

The Systems Control Group at the University of Luxembourg focuses on 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. This project is inserted within the framework of the interdisciplinary Doctoral Training Unit NextImmune (https://www.lih.lu/page/nextimmune-dtu). Data will be obtained from another group at LIH, and the role of the PhD candidate is to use that data and established computational tools to identify potential regulatory causality between genes in Th2 cells. This will provide a directed network of cause-effect relationship between measurements (genes).

YOUR PROFILE

• Hold (or being about to obtain) a Master degree in Mathematics, Theoretical Physics, Control Systems Engineering, Theoretical Machine Learning or related fields.
• Strong mathematical background is a requirement. Biological knowledge is not essential.
• We will only consider students that graduate in their top 20% undergraduate and Master’s class rank (equivalent to a UK first class degree).
• Excellent working knowledge of English.

Applications (to be sent online only) should contain the following documents:

• A detailed Curriculum vitae that includes your class rank.
• A motivation letter, including a brief description of past research experience and future interests.
• Copies of diploma and transcripts of Bachelor/Master.
• Please ask at least two references to email their confidential letters directly to Mrs Sofia Pereira (sofia.pereira@uni.lu) within two weeks of submitting the application.

Only complete applications will be considered.

Review of applicants will begin immediately and will continue until the position is filled.