About the team/job
The European Molecular Biology Laboratory (EMBL), one of the highest ranked scientific research organizations in the world, is looking for an Imaging Mass Spectrometrist, a staff member who will actively participate in the development, evaluation, optimization, and application of MALDI-imaging mass spectrometry methods.
This position is open in the Alexandrov Team within the ERC Consolidator project METACELL on spatial single-cell metabolomics as well as an OpenTargets project (https://www.opentargets.org/) on investigating metabolism of immune cells in collaboration with other groups at EMBL, the Wellcome Sanger Institute, Sanofi and other companies including Celgene, GSK, and Takeda.
Your responsibilities will include developing, optimizing, evaluating MALDI-imaging mass spectrometry methods on a cutting-edge MALDI-imaging system (AP-SMALDI2-Orbitrap with 2 μm pixel size) and applying them in particular to immune human cells. You will also be engaged in interdisciplinary work together with data scientists and software developers to improve METACELL, METASPACE and other software tools and platforms developed by the Alexandrov Team. In the framework of the ERC and OpenTargets projects, you will collaborate with other scientists internally at EMBL and externally, in particular at Wellcome Sanger, on integrating MALDI-imaging with cutting-edge single-cell technologies, including RNA-seq and metabolomics.
We are looking for a university graduate with a degree in Analytical Chemistry or related disciplines. Essential qualifications include experience in imaging mass spectrometry for metabolites, small molecules and/or lipids. Willingness to work in a small highly-interdisciplinary team is required.
You might also have
Having one of the following would be a plus: proficiency specifically in MALDI-imaging mass spectrometry and/or using Orbitrap-HRMS for non-spatial metabolomics; knowledge of mammalian metabolism and/or experience of working with mammalian cells; hands-on experience in brightfield and fluorescent microscopy. The basic knowledge of programming or scripting is helpful but not required immediately.
Why join us
You will be a critical part of a dynamic, interdisciplinary, international and cross-cultural team where we work at the intersection of biology, chemistry, and computer science. Our team currently includes 7 scientists and 3 software developers. We develop integrative computational and experimental methods for spatial metabolomics to detect metabolites in tissues and cells and interpret this molecular data in light of the spatial context. We strive to provide a healthy work environment with a flat hierarchy supporting a diversity of opinions, with freedom to make decisions and with funded opportunities to grow professionally.
What else you need to know
EMBL is an inclusive, equal opportunity employer offering attractive conditions and benefits appropriate to an international research organisation with a very collegial and family friendly working environment. The remuneration package comprises from a competitive salary, a comprehensive pension scheme, medical, educational and other social benefits, as well as financial support for relocation and installation, including your family and the availability of an excellent child care facility on campus. Please note that appointments on fixed term contracts can be renewed, depending on circumstances at the time of the review. The knowledge of German is not required.
Open Targets is a pioneering public-private partnership between EMBL, EMBL-EBI (European Bioinformatics Institute), GlaxoSmithKline (GSK), the Wellcome Sanger Institute (Sanger), Celgene, Sanofi and Takeda, located on the Wellcome Genome Campus in Hinxton, near Cambridge, UK. Open Targets brings together expertise from six complementary institutions to generate evidence on the biological validity of therapeutic targets and provide an initial assessment of the likely effectiveness of pharmacological intervention on these targets, using genome-scale experiments and analysis. Open Targets aims to provide an R&D framework that applies to all aspects of human disease, to improve the success rate for discovering new medicines and share its data openly in the interests of accelerating drug discovery.