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.
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
Contract Type : Contrat à durée déterminée
Work Hours : Temps plein 40.0 Heures par Semaine
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
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.
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For further information, please contact : Enrico Glaab
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