Pablo Lopez-Tarifa obtained his PhD degree in Theoretical Chemistry in a collaboration between the Universidad Autónoma de Madrid and the Universitéd’Evryvald’Essonne (Paris, France). In his thesis, he pursued the simulation of ultrafast reactions occurring in ion-collision experiments via TDDFT simulations. In 2011, he joined the Laboratory of Computational Chemistry at the EPFL (Switzerland) where he developed theoretical methodology to describe excited state dynamics of systems under the presence of extreme intense short pulses. In 2015, he joined the departments of Theoretical Chemistry and Biophysics at the Vrije Universiteit as a part of Solardam consortium, where he used the eScience Python library QMflows to automatize quantum chemistry calculations designed to study the light absorption of natural chromophores. In 2017, he was hired by Spanish Research Council (CSIC) to work in close collaboration with Simune Atomistic Co., improving and expanding the applicability of parallel codes for material science research.
In 2019, Pablo joined the Netherlands eScience Center as an eScience engineer.
Konrad is a second year master student of Computer Science (joint degree at VU and UvA) in the track of Big Data Engineering. During his studies he enjoyed courses of Data Processing, Machine Learning and Distributed Systems. He graduated from Warsaw University of Technology with BSc degree in Electronics Engineering in Medicine where he also gained knowledge in Radiology, Nucleonics and Detection and Processing of Nuclear Signals.
At the Netherlands eScience Center Konrad will join the Real Time Neutrino Detection project working on GPU data processing pipeline.
Kalaivani recently completed her PhD in Computer Engineering from the University of Florida. Her dissertation research focused on the analysis of a person's linguistic style as a behavioral biometric trait. She completed her MS in Electrical Engineering from Clemson University, USA and B.Tech in Instrumentation from Anna University, India. Her research and work experience involves Machine Learning applied to Computer Vision and Natural Language Processing problems
Johan holds degrees in journalism and communication science, history and international relations. From 2003 to 2005, he worked as a print journalist at Naspers media in South Africa, covering crime and criminal court proceedings.
In 2011, he obtained his Master’s degree from the University of Amsterdam, where over the past 8 years he has continued working in various roles as senior communications adviser, press officer and chief speechwriter for the UvA Executive Board. Johan joined the Netherlands eScience Center in June 2019.
Sarah is a researcher/analyst in Geomatics and Remote Sensing. Her research interest is the use of Earth observation data and geostatistics to describe the interaction between weather, land, and water.
She has a BSc. in Geodesy & Geomatics - Surveying Engineering, and a MSc. in Remote Sensing (K.N. Toosi University of Technology, Iran). During her Master’s studies, she investigated the use of spatial unmixing for image fusion. She was involved in two national projects in Iran; a rice production monitoring system, and an irrigation advisory system. She moved to the Netherlands as a highly skilled migrant and did her Ph.D. in geostatistics and copulas, a relatively new area for integrating of information (Departments of Earth observation science, and Water resource science, the faculty of ITC, University of Twente).
She has some experience in lecturing, supervising students and preparing education material for data assimilation and copulas. She has particular skills in programming, system analysis, geo/statistical methods, fusion techniques, image/data processing and management, optimization and simulation methods.
• Scientific Computing
• Modelling Physics and Astronomy
• Computational (cell)Biology
• Scientific Visualization
Modelling Physics and Astronomy
After his Bachelor Physics and Astronomy and BSc project on modelling plasma light emission in Tokamak reactors, Jaro did a master in Computational Science that he obtained at the UvA in 2017. For his master thesis he worked on the parameterization of subgrid processes in atmospheric flow at the KNMI. He has very broad scientific interest ranging from cell biology to plasma physics and from modelling physical systems to machine learning and scientific visualization.
At the eScience Center he works on eWaterCycleII and other related projects.
Mariëtte van der Zande studied Business Administration (major in Accounting) at the University of Groningen including a semester at the Ajou University in Suwon, South Korea. After graduation she worked in different finance roles for Deloitte Accountants, SNV Netherlands Development Organisation and VBK Uitgevers.
Prem Rajaram worked several jobs in the banking sector. First as financial support and then, for the last ten years, IT support. He also coached young people towards getting their driver's license.
• High Performance Computing
• Heterogeneous Computing
• Performance Modeling
• Java / Python / C++ / CUDA
High Performance Computing
Java / Python / C++ / CUDA
Souley Madougou was born in Niger. Souley attended Mohamed I University of Oujda studying mathematics and physics, followed by computer science at the Cadi Ayyad University of Marrakech.
After an internship and a bachelor degree in computer science he received his Master degree in computer science in 2002 at the University of Orleans followed by a PhD in parallel computing on PC cluster and virtual reality in 2005.
On behalf of ClusterVision, Souley moved to the Netherlands. He worked as a parallel computing consultant and developer of their cluster management tool. He developed in many languages, including C++ and Perl. He ended up joining PCC, a UvA spin-off, where he did R&D in diverse data integration and provenance projects. Souley later joined the AMC hospital to concretely apply provenance to workflow execution on grid infrastructures for a better control and for reproducibility of the results. He then joined the UvA to work in the Generic eScience project, especially on LOFAR data processing and the design and development of tools for optimal use of modern parallel architectures. Finally, Souley worked briefly on the EDISON project aiming at building the profession and curriculum of data science in Europe where he looked at validating certain results obtained manually using various machine learning techniques.
• Data Handling & Access
• Data Pipelines
• Data Analytics
• Statistical Modelling
• Machine Learning
• Physics & Astrophysics
• Scientific Methods
Data Handling & Access
Physics & Astrophysics
Meiert Grootes studied physics with a minor in mathematics at the Christian-Albrechts-University of Kiel, Germany, specializing in astrophysics. His diploma thesis focussed on studying the evolution of accretion disks around super-massive blackholes exploring the effect of the host galaxy potential and generalizations of Newtonian gravity; work that was based on grid-based hydrodynamical simulations in FORTRAN.
For his PhD he went to Heidelberg, Germany, also becoming a member of the Galaxy And Mass Assembly survey consortium (GAMA) for which he designed and implemented the bespoke UV photometry pipeline. The further focus of his research initially lay on developing a star-formation rate unbiased classifier of galaxy morphology and a method of applying radiative transfer models to recovering the intrinsic spectral energy distribution of large statistical samples of galaxies, then shifting to applying these tools to empirically probing the fundamental process of gas-accretion by galaxies, commonly referred to as gas-fuelling.
After defending his thesis in 2013, he accepted a position as postdoctoral researcher at the Max-Planck Institute for Nuclear Physics, where he continued his research into gas-fuelling, focussing on empirically constraining how and to what extent the larger scale environment impacts the ability of satellite galaxies to accrete gas. Using the full multi-wavelength photometric and spectroscopic database and MC models they showed that, contrary to the standard paradigm, their gas-fuelling is largely unaffected.
In 2015 he then joined the European Space Agency as an independent fellow, where he focussed on the evolution of the dust content of galaxies, as well as on combining weak-lensing based direct constraints of galaxy dark matter halo mass using Bayesian MCMC models with his established methods to probe gas-fuelling. Focussing on the halo mass dependence of gas fueling for central galaxies and the evolution of the relation between galaxy star formation rate and stellar mass, one of the fundamental empirical relations of extragalactic astrophysics.
Together with his collaborators he presented evidence for tension between the currently favored model and the data available from modern surveys and have provided the basis for a sensitive test of the model with upcoming observational facilities such as the James Webb Space Telescope.
Merijn studied Computer Science at the Vrije Universiteit (VU) in Amsterdam, following the High-Performance Distributed Computing track supplemented with as many theoretical CS courses as would fit. During his studies his main interests were (functional) programming languages, compilers, and distributed systems.
In the last year of his degree he went to the Universiteit of Amsterdam to do the compiler course, where he stuck around to do his master project on the S-Net coordination language, combining his interests in programming languages, compilers, and distributed systems into a single project. After his degree he stayed at UvA, joining the ADVANCE EU project as research assistant, later continuing this work at Heriot-Watt University in Edinburgh.
In 2014 he moved back to the Netherlands to start a PhD in graph processing on GPUs at the UvA. This work focussed on the relationship between the structure of the input graphs and the performance of algorithm implementations on the GPU. The goal being to predict the fastest implementation of an algorithm for a given input and being able to switch between implementations at runtime if this changes at runtime. He’s currently finishing up his thesis on this research.
• Scientific Computing
• Computational Fluid Dynamics
• Solid Earth Modelling
Computational Fluid Dynamics
Solid Earth Modelling
Maria received her BSc in Geology and MSc in Geophysics from Novosibirsk State University, Russia. During 2009 - 2017 she has been working first as PhD Candidate and later as a PostDoc at University of Utrecht, faculty of Geosciences.There she has been working on 3D numerical modelling of subduction evolution in Western Mediterranean region. This research resulted in numerous publications in highly-cited journals and oral presentations at international conferences. One of the accomplishments was creating of the first in the world full 3D numerical model of a subduction region which was later extended with integration of present day seismic observations. She enjoys working on complex tasks in numerical modelling domain and she likes to implement her out-of-box thinking capabilities in solving issues inside as well as outside of her core competence.
• High Performance Computing
• Numerical Analysis
• Algorithm Development
High Performance Computing
Adithya is a computational scientist at heart. He graduated from Friedrich Alexander University Erlangen, Germany and KTH, Stockholm with a Dual Masters degree in computational engineering and scientific computing with a specialization in CFD. During his masters course he developed massively parallel programs and GPU parallel programs to simulate fluid using grid based and particle based simulation techniques.
During his PhD at AMOLF and University of Amsterdam, he developed a new computational technique called MD-GFRD to simulate reaction-diffusion systems. MD-GFRD combines Green’s Function Reaction Dynamics (GFRD) for simulating the system at the mesoscopic level where the particles are far apart, with a microscopic technique such as Molecular Dynamics (MD) for simulating the system at the microscopic scale where they are close together. This scheme describes for the first time how a microscopic technique can be seamlessly integrated with a mesoscopic technique, thus setting up a true multi-scale scheme that can achieve the same microscopic resolution as that of a purely microscopic technique, yet is orders of magnitude faster when the concentrations are low.
• Biological physics
• Statistical modeling
• Data Analytics
• Machine learning
In terms of academic research, Florian comes from a physics and cell biology background. He studied physics in Leipzig, Germany and Marseille, France. In Leipzig, he then did his PhD in the field of biological physics. The main focus of his work was on the spatial and functional self-organization within living cells. He moved to Amsterdam in 2012 where he continued with related research projects as a postdoctoral researcher at AMOLF, and later at the TU Delft. Throughout all those research activities Florian always worked in-between computer simulations and experiments that he developed, performed, and analyzed.
After his postdoc Florian felt that it was time for a change. He made an outgrown hobby his new profession and founded a small company (KÄNDI) in Amsterdam to develop and manufacture sustainable, high-quality sweets. As much as he enjoyed the creative side of artisanal work and product development, and as much as his kids loved that he was working with sweets and chocolate, he kept missing more complex scientific questions as well as the open exchange of ideas and knowledge within a scientific community. In 2018, after two years of doing very analog work as a profession and digital work in his free time (machine learning, visualization), Florian hence decided to switch the order and rather keep the analog part for his free time.
• Web Application Development
• Mobile Application Development
Web Application Development
Mobile Application Development
Pushpanjali obtained her BSc and MSc in Computer Science at the Pune University, India. She started off her career as Software Developer and since then worked at various companies, across functions like software development, iOS development and frontend development.
During 2015 – 2016 she was working as Junior Software Developer in Vidushi Infotech, after that she worked as iOS Developer in Exult infotech in Pune.
At the eScience center Pushpanjali is working on Visual Storytelling and EYRA benchmark projects.
Kim obtained her MSc degree in Economics from VU University with a specialization in Marketing.
Before joining the Netherlands eScience Center, Kim worked at Reed Elsevier as a Marketing Manager responsible for a portfolio of scientific journals across various disciplines such as Health Science, Life Science, Social Sciences & Humanities.
• Scientific Computing
• Web Development
Evert completed his PhD in astrophysics at the University of Amsterdam, on the topic of gamma-ray bursts. After that he has occupied several postdoctoral positions on observational astronomy, amongst others in the UK and Australia. Over time his activities has focused on the development of reduction and analysis software for telescope observations.
At the eScience Center, he works on combining distributed datasets in an easy-to-access fashion for researchers, within the European Climate Prediction system project.
Arnaud de Jong is Chief Executive Officer of Airbus Defence and Space Netherlands B.V., the largest space company in the Netherlands and supplier of high-tech products and services for the international space market. In addition, Arnaud is Head of the Cluster Solar Arrays, Systems & Services within the Space Systems programme line of Airbus Defence and Space, and with that responsible for all Solar Array activities in Leiden and Munich, for the product lines Launcher Structures, Instruments & Systems and Thermal-Mechanical Products in Leiden and for Compact Range activities in Munich. In his position Arnaud manages a team of around 300 space engineers in Leiden, the Netherlands, and a team of 120 aerospace professionals in Munich, Germany.
Before taking up his position as CEO of Airbus Defence and Space Netherlands, Arnaud held several positions worldwide, working and living in four countries since 1996. He started his career at Coopers and Lybrand. In 1999 he became Senior Manager in the Mergers & Acquisitions Department of Daimler Chrysler Aerospace HQ in Munich. After the merge of Daimler Chrysler, Matra and Construcciones Aeronáuticas into the global pan-European aerospace and defence corporation EADS (today Airbus), he held several positions within the Airbus organisation in Paris and Munich. In 2002, he was appointed Chief of Staff of the CEO of Airbus Defence and Security, Munich, Germany. In 2005, Arnaud joined the business unit Military Air Systems as Head of Strategy and Technology Management, which later on included operational responsibility for all Pilot-Training and flight operations as well.
Arnaud de Jong graduated as Master of Business Administration at The University of Groningen, studied at Business School École Supérieure de Commerce in Montpellier, France and completed his study with a scholarship in Montreal, Canada. In addition to his daily commitment to the teams of Airbus, Arnaud is responsible for the roadmap Space within Holland High Tech and member of several advisory councils (e.g. Delft University of Technology, TNO Industries and the Netherlands eScience Center).
• Parallel Algorithms
• High-performance computing
• Distributed computing
• Many-core accelerators
Stijn obtained his MSc degree in Computer Science from VU University, with a specialization in High-Performance Computing. His master thesis focused on the performance and scalability of community detection, a type of graph analysis where the goal is to split the dataset into cohesive components. During his thesis, he several developed multi-core and many-core methods for graph processing.
Before joining the Netherlands eScience Center, he worked at Delft University of Technology and University Twente on various graph-processing research projects.
His research interests lie in parallel algorithm design, large-scale distributed/parallel processing, and GPU programming.
Aletta has a PhD in Biology (2007) and has worked for many years in research management for different scientific disciplines ranging from Linguistics to Physics. She has more than ten years of experience in the field of research innovation and impact.
She has been a consultant and non-scientific coordinator of large collaborative European projects at NEN (2007) and the VU (2010). In 2013 she joined the University of Leiden as Senior advisor research funding and became Director Knowledge Partnering of the TTO in 2015. In this function she managed a team of six advisors that linked research ideas and innovations to (societal) impact by using partnering, business development, grants and entrepreneurship to increase the research income & impact of the university and medical center.
In 2016 she became the Managing Director of a 100 MEuro new Advanced Research Center (ARC CBBC) and helped to build up the center. For this public private partnership of three universities and Shell, AkzoNobel and BASF, she was responsible for coordinating and implementing the strategic plan, managing HR, PR and finances and the setting up of the research and education program of the Center.
Aletta has a special interest in female entrepreneurship and gender balance. She organized and gave a workshop on gender balance at Kyoto University, Japan in 2017, is active in a female entrepreneurship network and is invited as reviewer for the EC in 2018.
In November 2017 Aletta joined the eScience Center as Director Operations.
• Scientific computing
• Parallel & distributed HPC methods
• Numerical modelling
• Python/ C/ Fortran
Parallel & distributed HPC methods
Python/ C/ Fortran
Inti has a background in astrophysics and has published on topics reaching from numerical cosmology, galaxy dynamics, stellar cluster formation to the evolution of planetary systems.
He obtained his PhD from Leiden University. After his PhD Inti did a postdoc at CMU in Pittsburgh on cosmological structure formation. Back from the US, he joined the development of the astrophysical multi-purpose software environment (AMUSE). He developed this research grade software package to facilitate coupled multi-physics and multi-scale numerical simulations. AMUSE is used by students and researchers worldwide to formulate and conduct numerical experiments in astrophysics.
His interest in the development of efficient and easy to use methods for coupled simulations led him to head a cross-disciplinary effort to transplant the technology developed as part of the AMUSE project to the oceanographic and climate science domains. This effort, funded by the Netherlands eScience Center, resulted in the development of the OMUSE coupling framework.
Inti's main expertise lies in the field of scientific computing, with extensive knowledge about parallel HPC methods, distributed computing and numerical simulation methods.
• Molecular Simulations
• Energy Research
• Quantum Chemistry
• Numerical methods
• Programing Languages: Python, C, Fortran
Programing Languages: Python, C, Fortran
Nicolas obtained a PhD in Nanoscience from University Paul Sabatier, Toulouse, France. During his PhD he studied new solutions for molecular quantum computing, or in simple words teaching single molecule how to count. In 2010, he joined the Theoretical Chemistry Department of Northwestern University where he studied how energy and electric charges propagate in biomolecules such as DNA and light harvesting complexes. He then moved in 2013 to the chemical Engineering Department of Delft University of Technology where he studied new ideas for solar energy research and molecular electronics.
Nicolas has developed different scientific software packages for various applications ranging from quantum transport to the calculation of electronic structure and electronic dynamics of molecular systems. He also has a keen interest in scientific visualization and illustration, statistical analysis of scientific data and the application of deep learning techniques to molecular science.
Nicolas joined the eScience Center in August 2017 as a research engineer.
• Semantic Web
• Recommender Systems
• Linked Data
• Data Analytics
In the last five years, Valentina has been a PhD student affiliated with the Web & Media Group (VUA Computer Science Department), supervised by prof. Guus Schreiber, and by prof. Lora Aroyo.
The focus of her PhD is on the use of Semantic Web technologies to enhance Recommender Systems. In particular, Valentina investigated how to improve the description of the items to recommend with information gathered from different Linked Data sources.
The objective of Valentina's research is to improve the serendipity of recommendations. During the last year, she has also been employed by Huygens ING as a scientific programmer, where she developed a tool to enrich historical data with Linked Open Data sources.
• numerical algorithms implementation
• functional programming
numerical algorithms implementation
Felipe did his PhD thesis on computational photochemistry, specifically on the dynamics of molecules in excited state. Since then Felipe has been developing software for scientific applications using a functional programming perspective.
He already collaborated with the eScience Center during the past 2 years, being a postdoc on the Computational Chemistry made Easy project.
Felipe is particularly focused on the implementation of numerical algorithms using Numpy and workflows in quantum chemistry using Noodles.
• Mathematical Modelling
• Evolutionary Biology
• Game Theory
Laurens studied Theoretical Physics and Economics and did some research in Evolutionary Biology. His main interests lie in Mathematical Modelling and trying to understand 'mechanisms', in particular using Game Theory.
Laurens has previously worked as a software engineer and as a consultant, but he missed the academic challenges at these jobs. The diverse projects at the eScience Center are more interesting and fun!
• Statistical modelling
• Machine learning
• Astronomy and planetary science
Astronomy and planetary science
Yifat has a bachelor degree in Physics from Ben-Gurion university (Israel) and a master in Physics from Tel-Aviv university (Israel), studying gravitational lensing in galaxy clusters. She received her Ph.D. in Planetary Science (Tel-Aviv university), where she focused on studying detection methods for transiting extra-solar planets. In the course of her research she became interested in statistics and algorithms and developed innovative methods for predictive modeling. These methods can be used to increase the yield of transiting planets from low-cadence surveys.
After moving to the Netherlands, Yifat continued to a post-doc position at the exoplanets group in the institute of Astronomy in the University Van Amsterdam, where she worked on statistical analysis of planetary atmospheres. Aside from planets, she is interested in machine learning, Bayesian inference, and algorithms.
Yifat joined the Netherlands eScience Center in summer 2017.
• Scientific Programming
• Efficient Computing
• Python, C
Bouwe studied at the of University of Amsterdam where he obtained a BSc in physics, an MSc in astronomy and an MSc in theoretical physics.
His astronomy master’s project was on estimating and modelling gravitational waves emitted from neutron star thermonuclear bursts, while his physics master’s project was a theoretical study on extending the standard model of particle physics with right handed neutrinos and a heavy gauge boson.
After graduating, he started working in the space industry, where he developed software for processing image data acquired by earth observation satellites for KNMI and ESA.
Among other things, he implemented improvements to the algorithms used in the data processors, increasing the accuracy and dramatically reducing the processing time. He is most experienced in the languages Python and C, but very interested in learning new languages and programming concepts. His main research interest is applying advanced computational techniques to solve real world problems, e.g. in medical science, environmental science, or developing safer and greener technology.
Tom obtained his BSc and MSc in physics (track Particle Physics) at the University of Amsterdam. For his thesis he worked on technology behind proton radiography, a method that can possibly improve the accuracy of proton radiation treatment of tumors.
Tom has always had an interest in computer programming and enjoys using his skills to solve practical problems. He is especially familiar with web standards and joined the eScience Center to help in projects with web related problems.
• Fluid Mechanics
• Computational Fluid Dynamics
Computational Fluid Dynamics
Yang obtained his bachelor in Dalian University of Technology, China. Major in Naval Architecture and Ocean Engineering, Yang found himself of great interest in fluid mechanics and numerical modeling. He extended his interest in the field of Computational Fluid Dynamics (CFD) and received his master in Delft University of Technology, Netherlands. His master thesis was finished in Maritime Research Institute Netherlands (MARIN), with a topic of the research on Vortex Induced Motion (VIM) of offshore platforms through CFD.
In 2017, Yang joined the Netherlands eScience Center. Serving as a PhD candidate, Yang works on the Blue Action project, under the EU Horizon 2020 Work Programme. The aim of the project is to gain more understanding about the Arctic weather and climate. Yang mainly focus on the atmospheric and oceanic energy transport towards the Arctic region. The access to high resolution numerical climate models and latest reanalysis datasets enables him to study the Arctic climate and improve the weather prediction.
Meanwhile, he also works in the Wageningen University (WUR).
• Computer vision
• Image processing
• Medical image analysis
• Algorithm validation
• Grand challenges
Medical image analysis
Adriënne has a bachelor degree in computer science and a master degree (cum laude) and PhD degree in biomedical image science.
Her PhD research at the image sciences institute (ISI) in the UMC Utrecht focused on image processing to reduce the X-ray radiation dose in computed tomography (CT) scans while maintaining image quality. She developed three noise reduction methods (one for 3D and two for 4D data) to improve the image quality of CT scans acquired with low radiation dose. As well as a method to derive vascular information from cerebral 4D CT perfusion (CTP) scans that has the potential to replace the additional CT angiography (CTA) scan.
As a post-doc at the biomedical image analysis group (BIGR) in the Erasmus MC (Rotterdam) she focused on noise reduction in 3D XperCT scans acquired with the C-arm CBCT system and compressed sensing, after which she returned to the ISI for her post-doc research on quantitative analysis of MR brain scans for cerebrovascular disease management.
During her post-doc research she developed an interest in grand challenges ( https://grand-challenge.org/All_Challenges/), which are open scientific competitions that use evaluation data and metrics to rank the performance of algorithms with respect to an objective. She has organized the MICCAI (http://www.miccai2013.org/) grand challenge on MR brain image segmentation (MRBrainS) workshop in Nagoya (Japan) and has set-up and maintains the open MRBrainS challenge evaluation framework (http://mrbrains13.isi.uu.nl/). At IEEE ISBI 2015 (http://biomedicalimaging.org/2015/) in New York, she organized the challenge workshop on neonatal and adult MR brain image segmentation (neatbrains15.isi.uu.nl). She is chair of the challenge workshops at IEEE ISBI '16 and '17 and co-organized the tutorial on designing benchmarks and challenges for measuring algorithm performance in biomedical image analysis at IEEE ISBI '16. At the NFBIA Summer School 2015, she gave a workshop on designing challenges in biomedical image analysis.
She was initiator and organizer of the ImagO colloquium series on medical imaging for the PhD programme of the graduate school of life sciences in the UMC Utrecht and was in the program committee of the international workshop on machine learning in medical imaging (MLMI) '15 and '16 at MICCAI.
In October 2016, Adriënne joined the Netherlands eScience Center as an eScience coordinator.
Her research is currently focussed on representation learning and designing a theoretical framework for grand challenges in biomedical image analysis.
Tom holds a PhD in Communication Science. He has studied Communication Science (MSc) and Journalism (MA) at the University of Amsterdam. The emergence and impact of new ICT and media technologies has always been a key theme in his work. After working as a television and newspaper journalist, he has been a PhD candidate and a lecturer at the University of Amsterdam and has been involved in various research projects in the field of social media, journalism and politics. Between 2012 and 2016, Tom worked as a researcher and consultant at the department Strategy & Policy of the Information Society of TNO. He has been involved in national and international research projects related to technology acceleration, smart industry, entrepreneurship, big data, privacy and telecommunication. Furthermore, Tom is the co-author of the Handboek Nieuwe Media (Handbook New Media) and is a mentor for the tech accelerator Startupbootcamp Amsterdam.
• Monte Carlo simulations
• Tomographic image reconstruction
• Proton therapy and radiation detection technologies
Monte Carlo simulations
Tomographic image reconstruction
Proton therapy and radiation detection technologies
Faruk has a bachelor degree in Engineering Physics and a MSc degree in Experimental Particle Physics. During his MSc he has worked for CERN ATLAS TRT group and was involved in software development as well as detector R&D efforts.
After completing his MSc, Faruk started his PhD at Ghent University and he has worked for ENVISION project which aims to develop novel imaging systems for hadrontherapy. Faruk is finishing his PhD at the Center for Advanced Radiation Technology (KVI-CART) of the University of Groningen. During his PhD, Faruk has been involved in Monte Carlo simulations of proton therapy and related TOF-PET-imaging. He participated in experiments related to proton therapy at the cyclotron facility of KVI-CART.
• Financial administration
• Management accounting
Noura studied bussiness economics at the Hoge School van Amsterdam. She finished her bachelor in 2014. During her study she did interns at the Belastingdienst and the Gemeente Amsterdam.’’
In February 2016 Noura joined the Netherlands eScience Center as Assistant Operations.
• High-performance computing
• Monte Carlo simulation
Monte Carlo simulation
Gijs van den Oord studied theoretical physics and mathematics at Utrecht University. In his master thesis, he investigated the relation between super-membranes and matrix models in string theory. After that he started a PhD in particle phenomenology at the Radboud University and Nikhef, where he developed expertise in high-performance computing, numerical simulation and the Monte Carlo method. With his C++ code he was able to simulate weak boson scattering in Higgsless models at the Large Hadron Collider.
After his graduation, Gijs has worked as a consultant in scientific software development. He has helped creating the DeltaShell framework at Deltares, embedding hydrological computational codes into object-oriented wrappers to facilitate visualization and coupling. Here he has also contributed to D-Flow Flexible Mesh, a shallow-water equation solver on unstructured grids.
Recently Gijs has started working on Primavera, a project with KNMI to study the EC-Earth climate model at high resolution, and a project with CWI and KNMI that aims to couple cloud-resolving large-eddy simulations to global atmospheric climate codes.
• Machine learning
• Big Data Analytics
Big Data Analytics
Dafne studied Computer Science and Mathematics at Utrecht University. During her master studies, she focused on Machine Learning and Data Analytics. Her master thesis was on recognizing product names using Conditional Random Fields, which she developed during her internship at VigLink in San Francisco.
After graduation, Dafne worked at ING as a Data Scientist, where she further developed her skills in Machine Learning and applied them to different business problems. She also got interested in distributed Machine Learning for big data sets, using tools like Spark.