[BBC] PhD/Postdoc vacancy: Development of deep learning algorithms for the identification of pathogenic species from single-cell MALDI-TOF MS spectra

[Willem Waegeman]

PhD/Postdoc vacancy: Development of deep learning algorithms for the 
identification of pathogenic species from single-cell MALDI-TOF MS spectra

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Duration of studentship: initially one year, extendable in case of a 
positive evaluation
Start date: flexible between October 2019 and January 2020

Application closing date: August 15th (will be extended if no suitable 
candidate is found). Apply as soon as possible to avoid disappointment!
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Project description:

Matrix-assisted laser desorption/ionization-time-of-flight mass 
spectrometry (MALDI-TOF-MS) is a well-known technology, widely used in 
species identification. Specifically, MALDI-TOF-MS is applied on samples 
that usually include bacterial cells, generating representative spectra 
for the various bacteria. In traditional MALDI-TOF MS systems, 
amplification of the bacterial load is performed by a culturing phase. 
In this project we will apply MALDI-TOF MS to individual bacterial 
cells, circumventing the need for culturing and isolation, accelerating 
the whole process. To this end, a large dataset with more than 50,000 
spectra is collected by the company BioSparQ. In the next step we intend 
to develop novel machine learning algorithms to analyze this data and 
perform single-cell identification. Due to the large size of the 
training dataset and the complexity of detecting patterns in MALDI-TOF 
MS data, we believe that deep learning techniques will be particularly 
useful in this context.

Background information:

The vacancy is available as a joint initiative between the research unit 
KERMIT of Ghent University (Belgium),under supervision of Prof. Willem 
Waegeman, and the company BioSparQ (The Netherlands), under supervision 
of dr. René Parchen. Both teams have already a collaboration.

KERMIT (acronym for Knowledge Extraction and Representation Management 
by means of Intelligent techniques) is a young interdisciplinary team of 
mathematicians, engineers and computer scientists, and itdraws upon 
intelligent techniques resulting from the cross-fertilization between 
the fields ofcomputational intelligenceandoperations research. The main 
focus is on mathematical and computational aspects of relational 
structures as knowledge instruments, with emphasis on the fields of 
fuzzy set theory and machine learning.KERMITserves as an attraction pole 
for applications in theapplied biological sciences, and serves 
colleagues in hydrology, ecology, bacterial taxonomy, genome analysis, 
integrated water management, geographical information systems, forest 
management, metabolic engineering, soil science, bioinformatics, systems 
biology, etc.

BiosparQ B.V. is a privately-held in vitro diagnostics company dedicated 
to provide healthcare professionals with a unique solution for rapid 
diagnostics of infectious diseases that improves patient outcomes, 
lowers healthcare costs and helps turn back. BiosparQ has focused its 
efforts on research into and the development of the Cirrus D20 medical 
diagnostic platform, based on proprietary DigiTOF^technology. This 
technology enables direct analysis of patient samples using a 
Single-cell MALDI-TOF approach.


The ideal candidate for the position has the following profile:

·An MSc or PhD degree in (Bio-)Engineering, Bio-informatics, Computer 
Science, Mathematics,Statistics,Physics, or equivalent – candidates from 
outside Belgium are welcome to apply.

·An interest for fundamental machine learning research, as well as 
practical applications in microbiology.

·In-depth experience with at least one programming language (Matlab, R, 
Python, Java, etc.)

·Good knowledge of deep learning methods is an asset.

·Fluent in English (speaking and writing, as demonstrated by personal 
texts).

·Knowledge of Dutch is an asset, but not a must.

·Team player with good communication skills.

·This position is available on a PhD and postdoc level, depending on the 
applications we receive.

·The person hired on this project is expected to travel between Ghent 
(Belgium) and Leiden (The Netherlands) on a regular basis.


How to apply
Send your c.v., a motivation letter, a copy of your MSc.- or PhD-thesis 
and/or any relevant publications to Ruth Van Den Driessche 
(ruth.vandendriessche at ugent.be <mailto:ruth.vandendriessche at ugent.be>).

-- 
Prof. dr. Willem Waegeman
Research Unit Knowledge-Based Systems (KERMIT)
Department of Data Analysis and Mathematical Modelling
Coupure links 653 9000 Ghent, Belgium
Phone:  + 32 9 264 92 00
Skype: willem.waegeman
www.kermit.ugent.be
users.ugent.be/~wwaegemn

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