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Doctoral Researcher in Computational Biology and
il y a 4 semaines
The **Luxembourg Centre for Systems Biomedicine (LCSB)** is an interdisciplinary research centre of the University of Luxembourg. We conduct fundamental and translational research in the field of Systems Biology and Biomedicine - in the lab, in the clinic and _in silico_. We focus on neurodegenerative processes and are especially interested in Alzheimer’s and Parkinson’s disease and their contributing factors.
The LCSB recruits talented scientists from various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly interdisciplinary and together we contribute to science and society.
The laboratory of Gene Expression & Metabolism is seeking a highly motivated doctoral student from an
experimental genetics background. Particularly, the student should be interested in identifying, designing,
and testing genomic modifications at high-throughput to understand the fundamental relationships
between how DNA variants lead to gene expression changes, and subsequent affect overall phenotypes.
The project will be in yeast, so prior experience with cell lines (and ideally with yeast) is necessary. Basic
benchtop biochemistry skills such as DNA, RNA, and protein extractions and basic quality control are a
prerequisite. Computational skills, such as basic bioinformatics and ability to read/program in R, are also
important, but can be developed further during the doctoral studies. Likewise, prior knowledge of genome
sequencing, transcriptomics, and/or proteomics are a bonus, but not a strict prerequisite for applicants to
this position. Likewise, the more knowledge the student has of modern biostatistics (e.g. correcting for
FDR, how to perform feature selection with various models like RF) the better, but extensive prior
knowledge is not a prerequisite. Prior knowledge of the fundamentals of biochemistry — particularly
carbon metabolism pathways and mitochondria — and genetics — e.g. how CRISPR works, how variant
impacts are predicted and assessed — are also important.
This research project has two main goals. The first is to use CRISPR to modify single point mutations in
different genetic backgrounds in yeast, and to then grow these different types of yeast in different carbon
environments and in different inhibitory chemicals, to see which mutations confer growth advantages. The
second goal is to study the gene expression (i.e. the transcriptome and proteome) to understand the
molecular pathways for how those point mutations result in a change in growth. The first phase of the
project will implement these DNA variants one-by-one, and afterwards the mutations will be implemented
at higher orders to create yeast with more pronounced growth phenotypes, and to understand
fundamental relationships in genetic regulation such as epistasis, additivity, and to experimentally test
how reliable predictive models of DNA variant impact work at high throughput (e.g. tens of thousands of
variants tested).
**Your Role...**:
In brief, the applicant should be from a biology or bioengineering background, but significant experience with bioinformatics or biostatistics (or at least the interest in developing these skills) will be seen favorably. Overall, the project will be roughly 66% wetlab biology work, and 34% bioinformatician/data analyst work, with the degree gradually shifting from more wetlab biology to more data analysis as the project develops (i.e. the first year’s work would be ~90% wetlab biology, versus only ~25% wetlab work in the final year of the project).
- A background in wetlab biology is necessary. The student should also be interested in learning computational methods
- Previous experience with population genetics, either in practice or in theory, is a bonus - particularly in yeast populations, but experience of studying populations in any species is good
- The more experience in programming and statistics, ideally in R, the better. However a computational / programming background is not strictly necessary
- Some experience with identifying nonlinear relationships in data, and/or with various modern methods for performing feature selection, is ideal
- Fluency in oral and written English
**Here’s what awaits you at the LCSB...**:
- **Excellent work environment** with state-of-the-art infrastructure, laboratory and administrative support
- **Truly connected. **We work together with hospitals and research institutes on a national and international level as well as industrial partners. Connection between science and society is very important to us. From our school lab - the Scienteens Lab - to the different outreach activities and collaborative partnerships with patient associations, we love to listen to society’s needs and share our passion for science
- **Be part of a multicultural team. **At the LCSB we have more than 50 nationalities. Throughout the year, we
