Doctoral researcher in Machine Learning / Bioinformatics for Biomedical Datasets

at University of Luxembourg
Published November 7, 2022
Location Luxembourg, Luxembourg
Category Machine Learning  
Job Type Scholarship  


Doctoral researcher in Machine Learning / Bioinformatics for Biomedical Datasets
(Valid from 01/11/2022 to 03/01/2023)

Language: English (UK)
Location Belval
Country: Luxembourg

Organisation LCSB
Job Number: UOL05366
Contract Fixed Term Contract
Duration 36 Month
Schedule Full Time
Work Hours 40.0 Hours per Week
Expected 01/04/2023
Start Date:

Functions: PhD Candidates
Job Doctoral Researcher

The University | About us…
The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The University was
founded in 2003 and counts more than 6,700 students and more than 2,000 employees from around the world. The University’s faculties and interdisciplinary
centres focus on research in the areas of Computer Science and ICT Security, Materials Science, European and International Law, Finance and Financial
Innovation, Education, Contemporary and Digital History. In addition, the University focuses on cross-disciplinary research in the areas of Data
Modelling and Simulation as well as Health and System Biomedicine. Times Higher Education ranks the University of Luxembourg #3 worldwide for its
“international outlook,” #20 in the Young University Ranking 2021 and among the top 250 universities worldwide.

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 machine learning scientist / computational biologist / bioinformatician (MSc level) who is experienced in applying statistical
learning algorithms to large-scale biomedical datasets and optimizing and evaluating prediction models. The candidate will conduct integrative machine
learning analyses of cellular imaging datasets, with a focus on applications in neurodegenerative disease research. This will include the development of
new structured machine learning approaches, the application of learning algorithms to complex biomedical data, and the joint interpretation of the data
together with experimental collaborators. The project will use new high-throughput data from patients, healthy controls, as well as in-vitro and in-vivo
disease models. The goal is to build models with improved predictivity for sample classification and improved interpretability to better understand
molecular and cellular perturbations in common neurological disorders. This project will be jointly conduced between groups from the computational field
and the biomedical field.

What we expect from you…
* The candidate will have a MSc or equivalent degree in biostatistics / machine learning, computational biology or bioinformatics
* Prior experience in large-scale data processing and statistics / machine learning is required, ideally with experience in the area of biomedical
imaging analysis
* Excellent communication and organization capabilities to facilitate the exchange between groups from different disciplines are essential
* A track record of previously completed courses and/or publications involving statistical and machine learning analyses of large-scale data (e.g.,
imaging data, omics) should be outlined in the CV
* Demonstrated skills and knowledge in biostatistics and biomedical data processing 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

We offer…

* An opportunity to join the Luxembourg Centre of Systems Biomedicine with an international and interdisciplinary work atmosphere
* Working in a scientifically stimulating, innovative, dynamic, well- equipped, and international surrounding
* Opportunity to work closely with international academic partners
* State-of-the-art research facilities and computational equipment

In Short…
* Contract Type: Fixed Term Contract 36 Month (extendable up to 48 months if required)
* Work Hours: Full Time 40.0 Hours per Week
* Location: Belval
* Employee and student status
* Job Reference: UOL05366

The yearly gross salary for every PhD at the UL is EUR 38028 (full time)

How to apply…
Applications should contain the following documents (combined into one pdf document):

* 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 formally through the HR system. Applications
by email will not be considered.

The University of Luxembourg embraces inclusion and diversity as key values. We are fully committed to removing any discriminatory barrier related to
gender, and not only, in recruitment and career progression of our staff.

In return you will get…
* 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. 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 (

Apply here


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