Doctoral researcher (PhD) in Computational Biology / Biostatistics (gn)

 

The University of Luxembourg aspires to be one of Europe’s most highly regarded universities with a distinctly international and interdisciplinary character. It fosters the cross-fertilisation of research and teaching, is relevant to its country, is known worldwide for its research and teaching in targeted areas, and is establishing itself as an innovative model for contemporary European Higher Education. It`s core asset is its well-connected world-class academic staff which will attract the most motivated, talented and creative students and young researchers who will learn to enjoy taking up challenges and develop into visionary thinkers able to shape society.

Within the University, the Luxembourg Centre for Systems Biomedicine (LCSB) is a highly interdisciplinary research centre (IC), integrating experimental biology and computational biology approaches in order to develop the foundation of a future predictive, preventive and personalized medicine.

Your Role

We seek a highly motivated computational biologist / bioinformatician (MSc level) who is experienced in the analysis of large-scale biomedical omics or neuroimaging data, using statistical methods and machine learning, and bioscientific data processing and programming. The candidate will conduct integrative machine learning analyses of biomedical data, focusing on molecular, neuroimaging and clinical data for neurodegenerative diseases. This will include the development of new structured machine learning approaches, the application of software to disease-related multimodal datasets, and the joint interpretation of the data together with experimental and clinical collaborators. The project will use new biological high-throughput data from patients, healthy controls, as well as in-vitro and in-vivo disease models. With the help of pathway-, network- and machine learning analyses, the goal is to improve the mechanistic understanding of molecular and cellular perturbations in common neurological disorders.

Your Profile

• The candidate will have a MSc or equivalent degree in computational biology, bioinformatics, or biostatistics / machine learning
• Prior experience in large-scale data processing and statistics / machine learning is required
• A track record of previously completed courses and/or publications involving analyses of large-scale biological data (e.g. omics, neuroimaging data) should be outlined in the CV
• Demonstrated skills and knowledge in next-generation sequencing data analysis, biostatistics, machine learning, pathway and network analysis are highly advantageous
• The candidate should have a cross-disciplinary aptitude, strong organizational and interpersonal skills, and a keen interest in collaborative biomedical research
• Fluency in oral and written English

In Short

• Contract Type: Fixed Term Contract
• Work Hours: Full Time 40.0 Hours per Week
• Location: Belval
• Student and employee status (36 months studies programme, as per university standards) with project funding available for up to 48 months
• 36 months fixed-term contract (renewable depending on thesis progress evaluation)
• Job Reference: UOL03604

Further Information

Applications should be submitted online and include:

• A detailed Curriculum vitae
• A motivation letter, including a brief description of past research experience and future interests, as well as the earliest possible starting date
• Copies of degree certificates and transcripts
• Name and contact details of at least two referees

Early application is highly encouraged, as the applications will be processed upon reception. Please apply ONLINE formally through the HR system. Applications by email will not be considered.

*gn=gender neutral.

Here’s what awaits you at the University

• Multilingual and international character. Modern institution with a personal atmosphere. Staff coming from 90 countries. Member of the “University of the Greater Region” (UniGR). 
• A modern and dynamic university. High-quality equipment. WiFi on campus. Close ties to the business world and to the Luxembourg labour market. A unique urban site with excellent infrastructure.
• A partner for society and industry. Cooperation with European institutions, innovative companies, the Financial Centre and with numerous non-academic partners such as ministries, local governments, associations, NGOs …

• Find out more about the University
• Addresses, maps & routes to the various sites of the University

Further information

For further information, please contact: Enrico Glaab

enrico.glaab@uni.lu

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