PhD Positions in Computational Analysis for Imaging Mass Spectrometry and Multi-modal Molecular Imaging
Faculty Mechanical, Maritime and Materials Engineering
Level: University Graduate
Working hours: 38.0 hours weekly
Salary: 2325 - 2972 euros monthly (full-time basis)
Faculty Mechanical, Maritime and Materials Engineering
The 3mE Faculty trains committed engineering students, PhD candidates and post-doctoral researchers in groundbreaking scientific research in the fields of mechanical, maritime and materials engineering. 3mE is the epitome of a dynamic, innovative faculty, with a European scope that contributes demonstrable economic and social benefits.
The department Delft Center for Systems and Control (DCSC) of the faculty Mechanical, Maritime and Materials Engineering, coordinates the education and research activities in systems and control at Delft University of Technology. The Centers' research mission is to conduct fundamental research in systems dynamics and control, involving dynamic modelling, advanced control theory, optimisation and signal analysis. The research is motivated by advanced technology development in physical imaging systems, renewable energy, robotics and transportation systems. http://www.dcsc.tudelft.nl
The Van de Plas lab is currently offering two PhD positions in computational methods for multi-modal molecular imaging, with a focus on imaging mass spectrometry and microscopy.
The lab is located at the Delft University of Technology (TU Delft) in the Netherlands, and is part of the Delft Center for Systems and Control. Our research activities lie at the interface between (i) mathematical engineering and machine learning; (ii) analytical chemistry and instrumentation; and (iii) life sciences and medicine. We explore new ways of acquiring, processing, and mining the massive data sets that imaging mass spectrometry and other molecular imaging modalities can produce. Research topics include:
- Signal processing (e.g. removal of noise, baseline correction, etc.)
- Dimensionality reduction and transformations (e.g. wavelet transform, dictionary learning, etc.)
- Pattern recognition and matrix factorizations (e.g. non-negative matrix factorization, convex optimization, etc.)
- High-level biological interpretation (e.g. automated anatomical interpretation)
- Data mining across different imaging sensors (e.g. data-driven multi-modal image fusion)
The lab has a strong network of international collaborators in both academia and industry. Collaborations include chemistry and instrument partners, such as the Mass Spectrometry Research Center and Caprioli lab at Vanderbilt University (Nashville, TN, USA), as well as medicine and biology partners, such as the Swinnen lab at the Department of Oncology of the KU Leuven University Hospital (Leuven, Belgium).
Our lab is part of several ongoing multi-disciplinary research projects. These include for example the Human BioMolecular Atlas Program (HuBMAP) of the United States’ National Institutes of Health, as well as SMART BRAIN, a FLAG-ERA JTC project through which Van de Plas lab is an associated member of Europe’s Human Brain Project Flagship.
Relevant publications from our lab:
- Van de Plas R., Yang J., Spraggins J., Caprioli R.M., Image fusion of mass spectrometry and microscopy: a multimodality paradigm for molecular tissue mapping, Nature Methods, vol. 12, no. 4, 2015, pp. 366–372.
- Verbeeck N., Yang J., De Moor B., Caprioli R.M., Waelkens E., Van de Plas R., Automated Anatomical Interpretation of Ion Distributions in Tissue: Linking Imaging Mass Spectrometry to Curated Atlases, Analytical Chemistry, vol. 86, no. 18, 2014, pp. 8974–8982.
- Cassat, J. E., Moore, J. L., Wilson, K. J., Stark, Z., Prentice, B. M., Van de Plas, R., Perry, W. J., Zhang, Y., Virostko, J., Colvin, D. C., Rose, K. L., Judd, A. M., Reyzer, M. L., Spraggins, J. M., Grunenwald, C. M., Gore, J. C., Caprioli, R. M., and Skaar, E. P., Integrated molecular imaging reveals tissue heterogeneity driving host-pathogen interactions., Science Translational Medicine, vol. 10, no. 432, 2018.
- HuBMAP Consortium (includes Van de Plas, R.), The human body at cellular resolution: the NIH Human Biomolecular Atlas Program., Nature, vol. 574, no. 7777, 2019, pp.187.
- Verbeeck, N., Caprioli, R., and Van de Plas, R., Unsupervised Machine Learning for Exploratory Data Analysis in Imaging Mass Spectrometry., Mass Spectrometry Reviews, 2019.
- A background in image & signal processing, machine learning, numerical analysis, or statistics. Applicants should have a MSc degree in Engineering, Computer Science, Systems & Control, Statistics, Computational Physics, or any field related to the lab’s research topics.
- Strong motivation to work in a multidisciplinary environment and interact with collaborators in medicine, biology, chemistry, and physics is essential.
- Good command of English is required.
- Candidates with experience in mass spectrometry, imaging, pattern recognition, or biotechnology are especially encouraged to apply.
Conditions of employment
The TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit graduateschool.tudelft.nl/ for more information.
Information and application
For more information about this position, please contact Dr. Raf Van de Plas ([email protected] ).
To apply, please submit an application package consisting of the following documents:
- a detailed curriculum vitae (and list of publications if available);
- a letter of motivation and research interests (up to 1 page);
- academic transcripts of all the exams taken and all the obtained degrees (in English);
- names and contact information of at least two academic references (e.g., project/thesis supervisors);
- a copy of up to three research-oriented documents authored by the applicant (e.g., thesis, conference/journal publications).
The expected start date is April 1st, 2020.
This call for applications will remain open until the ideal candidates are found. However, for full consideration please apply by January 31st, 2020.
For information about the selection procedure, please contact Irina Bruckner, HR-advisor, email: [email protected] .
Enquiries from agencies are not appreciated.
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