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University of Luxembourg

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Doctoral Researcher in AI & Bioinformatics University of Luxembourg in Luxembourg

Degree Level

PhD

Field of study

Computer Science

Funding

Available

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Country

Luxembourg

University

University of Luxembourg

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Keywords

Computer Science
Data Science
Biostatistics
Biology
Network Analysis
Artificial Intelligence
Computational Biology
Systems Biology
Neuropsychology
Medical Science
Pathway Analysis
Clinical Data
Neurodegenerative Disease
Statistics
Bioinformatic
Machine learning

About this position

The University of Luxembourg invites applications for a Doctoral Researcher position in AI & Bioinformatics at the Luxembourg Centre for Systems Biomedicine (LCSB). The LCSB is renowned for its interdisciplinary research in Systems Biology and Biomedicine, with a strong focus on neurodegenerative diseases such as Alzheimer's and Parkinson's. The centre brings together scientists from over 50 countries, fostering a collaborative and innovative research environment.

The successful candidate will join a vibrant team to conduct integrative analyses of large-scale biomedical datasets, with a particular emphasis on single-cell omics and clinical data. The research aims to predict clinical outcomes and identify therapeutic targets for complex neurological and cancer disorders. Key responsibilities include implementing and applying software analysis pipelines, performing statistical and machine learning analyses, and collaborating with experimental and clinical partners to interpret disease-related data.

Applicants should possess a MSc or equivalent degree in biostatistics, bioinformatics, computational biology, machine learning, or related fields. Essential qualifications include experience in large-scale data processing, statistics, machine learning, and omics data analysis. Additional strengths such as expertise in pathway and network analysis, single-cell data analysis, and familiarity with neurodegenerative disease biology are highly valued. Candidates must demonstrate at least B2-level proficiency in the language of their thesis and have strong organizational and interpersonal skills.

The position offers a fixed-term contract of 36 months, full-time employment (40 hours per week), and a competitive yearly gross salary of EUR 41,976. The University of Luxembourg provides a modern, international, and inclusive working environment with excellent infrastructure and close ties to industry and European institutions.

To apply, candidates should submit their application online via the university's HR system, including a CV, cover letter, transcripts, and contact details of at least two referees. Early applications are encouraged as the selection process is ongoing. The University of Luxembourg is committed to promoting equality and diversity among its staff and students.

Funding details

Available

What's required

Applicants must hold a MSc or equivalent degree in biostatistics, bioinformatics, computational biology, machine learning, or related subject areas. Prior experience in large-scale data processing and statistics or machine learning is required. Candidates should have demonstrated skills and knowledge in omics data analysis, biostatistics, machine learning, pathway and network analysis. Experience with single-cell data analysis and familiarity with neurodegenerative disease biology are advantageous. Applicants must demonstrate at least B2-level proficiency in the language of their thesis, with accepted certificates as specified by the university. Strong organizational and interpersonal skills, cross-disciplinary aptitude, and a keen interest in collaborative biomedical research are expected. Previous work and publications in bioinformatics analysis of large-scale biomedical data should be outlined in the CV.

How to apply

Submit your application online through the University of Luxembourg HR system. Include your CV, cover letter, transcripts, and contact details of at least two referees. Early application is encouraged as applications are processed upon reception. Applications by email will not be considered.

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