The PERICO research programme aims to uncover how a central metabolic organelle, the peroxisome, participates in controlling cellular metabolism. Metabolism and metabolic control are emerging as important frontiers in physiology. This is because, in our rapidly changing world, we face the effects of both metabolic extremes – from obesity on the one hand to malnutrition on the other. Learning how to control energy metabolism is therefore one of the most pressing challenges of the 21stcentury.
Peroxisomes are key metabolic organelles, which must communicate and interact extensively with their environment to exchange metabolites and coordinate cellular responses. Membrane contact sites (MCS), where membranes of two organelles are physically tethered to enable rapid transfer of small molecules, enable organelle communication and are crucial for coordination of cellular functions and hence human health. Research on organelle interactions and communication is a challenging, upcoming field in current cell biology.
PERICO will exploit recent developments in high-throughput and genome-wide screening technologies, combine these with modern molecular cell biology and systems biology and ultimately translate the data into new leads for drug discovery and therapy.
Early Stage Researchers
The training schemes include specific research projects, secondments to partner organizations, a wide range of dedicated courses, and workshops organized by the academic and industrial partners of the Network. The scientific training programme will be complemented with training in managerial soft skills.
The positions for Early Stage Researchers are available for candidates with a research experience ≤ 4 years (counted from the diploma that gives the rights to embark in a doctoral degree).
Candidates must not have resided or carried out their main activity (work, studies, etc) in the country of their host organisation for more than 12 months in the 3 years immediately prior to recruitment (short stays, such as holidays, are not taken into account).
Candidates should have:
- exceptional academic performance, including qualifications, prizes
- subject specific skills and expertise (see project descriptions)
- communication, presentation skills and team working abilities
- competence in written and spoken English.
Length of appointment: 3 years
Type of contract: temporary
Application deadline: 10-12-2018
Starting date: April 1, 2019
Applicants can apply for multiple positions.
Descriptions of the individual PhD projects
A PhD position is available at Lambert Instruments, Groningen, The Netherlands
Project title: Autonomous High-Throughput accurate FLIM with subcellular resolution
Development and optimization of automated data mining from multi-well microscopy plates.
The goal is to improve on current intensity-based methods for detection of the presence of biological phenomena in microscopic images by applying deep-learning for morphological analysis in detection and classification. Additional discriminating dimensions are created by integrating Fluorescence Lifetime Imaging Microscopy (FLIM) measurements into the dataset. The end point is a fully automated processing workflow to detect subtle changes in organelle morphology. The research involves improvement of a FLIM protocol for speed and accuracy, optimize modulation and illumination parameters, develop noise reduction algorithms. By using active feedback loops for real-time measurement adjustment, the harvest of target patterns will be optimized using reinforcement learning or other control algorithms for digital microscopes.
Location: Groningen, The Netherlands
Supervisor: Prof. Dr. L.R.B. Schomaker (l.r.b.schomakerATrug.nl); Mr. J. Wehmeijer (jeroenATlambertinstruments.com)
Co-supervisors: Prof. Dr. I.J. van der Klei, University of Groningen & Prof. Dr. M. Fransen, KU Leuven
Planned secondments: KU Leuven, University of Groningen
Required subject specific skills and expertise: a master’s degree in computer science or artificial intelligence with specialisation in image processing and (deep) machine learning. Experience with biological imaging techniques is advantageous but not mandatory.
Application deadline: 10/12/2018
Starting date: April 1, 2019
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