27 Postdoctoral Fellowship at Delft University of Technology (TU Delft), Netherlands

The researcher will work in a team of experimentalists and theorists who share the common goal to imaging at the nanometer scale. She/he will work on simulation/theory of image formation and parameter estimation. The image formation description is based on the so-called 4pi microscope where the self-interference of the fluorescent emission can be used to estimate the axial position of a single emitter with nano meter precision. To this end the emission light is split into 4 channels (by polarization beam splitters) and the respective intensities are indicative for the axial position. As long as the emitter is free to rotate during one camera frame, a rotational symmetric point spread function (PSF) will be recorded, but if the emitter is fixed (due to conformational embedding or freezing of the medium) the PSF will reflect the dipole character of the emission and will depend on the 3D orientation of the single molecule emitter. In addition (field dependent) aberrations will influence the shape of the PSF. This requires the estimation model to reflect the forward imaging process perfectly and include all relevant parameters, such that a fit with many free parameters still converges. We want to build on our expertise in (maximum likelihood) estimation theory in combination with Cramer-Rao lower bound analysis to find the best way to tackle the problem at hand. Based on the results, we can set requirements on the tolerances for e.g. the alignment of objectives and the beam path to ensure at the end the most optimal localization precision.

The researcher will work in a team of experimentalists and theorists who share the common goal to imaging at the nanometer scale. She/he will work as an experimentalist designing and performing experiments with cryo fluorescent microscopy. In order to achieve very high spatial resolutions from single molecule emitters in 3D will be use a so-called 4pi setup with two opposing objectives. In addition the wavefront of the light must not be disturbed by optical aberrations. In reality such aberrations are always present, but only at our targeted high resolution at cryogenic temperatures, do they play a crucial role. Therefore the candidate will incorporate adaptive optics instrumentation and algorithms to measure the wavefront distortion and subsequently correct the distortions. 

You will coordinate research activities to design, fabricate, characterize, and optimize the performance of graphene-based neural interfaces for multimodal interaction with brain tissue. You will be part of the vibrant environment of young researchers of the 10-year-long Dutch Brain Interfaces Initiative (DBI2) project, funded by the “Gravitation” programme of the Dutch Ministry of Education, Culture, and Science. The project aims to bring together a broad and diverse Dutch consortium with expertise in neuroscience, neurotechnology, and computer science to research brain interactions, specifically looking into understanding how each part, from neuron to brain region, interacts with the rest of the brain and with the outside world.

In this fully funded 3-year Postdoc position (UPSIDE EU grant – EIC Pathfinder Challenges), you will investigate novel system level architectures for energy and area-efficient FUS and EEG devices at the integrated circuit level, using advanced CMOS technologies. You will be embedded in the research group of Dr. Tiago Costa and Dr. Dante Muratore, and will have close collaboration with colleagues in both groups. You will also work closely with collaborators in the fields of microfabrication, microsystem integration and neurobiology. The outcome of your work will be tested in vivo towards unraveling the promising effect of FUS in the complex neural circuits involved in treatment-resistant depression.

The first postdoc will primarily work on the development and characterization of liquid and (semi)solid electrolyte formulations in combination with Li-metal anodes for use in all solid-state Li-ion batteries. This position is part of the academic industrial NXTGEN HIGHTEC project. The postdoc will characterize the materials prepared using both electrochemical and analytical techniques including NMR spectroscopy, neutron depth profiling (NDP) and X-ray/neutron diffraction as required. Previous experience working with Li-ion batteries as well as on one or more of these techniques is desirable but not a prerequisite. There is extensive expertise and experience within the hosting group on all of these techniques, providing ample opportunity for the applicant to build expertise efficiently. In addition, there is the opportunity to be involved in the material development part of these projects, especially concerning solid-state batteries and their interfaces.

The second postdoc will primarily work on the development of polymer based electrolytes for Li and Na ion batteries. This position is part of a project funded by the Dutch Polymer Institute. The postoc will synthesize the polymer based electrolytes and characterize them using electrochemical and spectroscopic methods including Raman and solid-state NMR spectroscopy. Previous experience on working with polymer based electrolytes is a prerequisite for this position. Experience on one or more of the characterization techniques while desirable is not essential as there is extensive expertise and experience within the hosting group on all these methods and ample opportunity to learn.

We are looking for a talented and motivated postdoctoral researcher to work on a cutting edge industrial academic collaborative project between HyET Lithium and TU Delft focused on the practical application of Si anodes in next-generation Li-ion (solid state) batteries. The task of the postdoc will be to characterize the Si anodes in full cells initially using liquid electrolytes (including recently developed electrolyte concepts) and at a later stage with next generation solid electrolytes. This will be done using a host of electrochemical and analytical techniques available in-house including SEM, XPS and (operando) NMR spectroscopy among others, with a focus on the study of the initial formation cycles as well as the SEI stability, which are critical parameters to achieve long term cycling of these Si-anodes.

IoT sensor nodes should have minimum form factor, low cost, accurate, and requires minimum maintenance, therefore, ideally environment powered. Getting sufficient energy from the environment then requires energy harvesters such as PV cells and highly efficient power converters. Such power converters must provide accurate MPPT, high conversion efficiency with a large power dynamic range, and a wide conversion ratio with minimum power consumption. Meanwhile, multi-input and output topologies will be preferred since they enable the use of multiple energy resources.

Advances in ultrasound now enable fast, volumetric and high-resolution imaging of living organs in intact and opaque organisms. However, ultrasound plays a relatively small role in the field of molecular imaging. To go further, one needs to interface ultrasound waves with biological processes occurring within cells. This project aims at using genetically encoded acoustic biomolecules to label specific cells in combination with 4D ultrasound imaging to reveal cellular activity at the organ scale.

This position is part of a collaborative project between the Delft University of Technology, University of Twente, and the University Medical Center Utrecht. The strategy of this SOUND-CHECK (see also: https://www.nwo.nl/nieuws/zes-projecten-van-start-open-technologieprogramma ) project is to make use of the potential of microbubbles to deposit drugs on the microscale level to treat head and neck cancer, including metastases. We will build new hardware (novel transducer technology, your work), and combine it with new biofabrication methods (3D printed phantoms) and new software algorithms (deep learning predictors) by the other partners to detect the unique nonlinear signatures of the microbubbles, to quantify the location and amount of drugs delivered, and to control and monitor the therapy.

Green hydrogen from water electrolysis is widely acknowledged to be a very important ingredient in the energy transition. Alkaline electrolysis is the most established and most economical way of producing green hydrogen. Ion Exchange Membranes are typically used to separate the generated hydrogen and oxygen, but until recently these were not successfully developed for alkaline conditions. However, strong improvements have recently been made and the resulting Anion Exchange Membranes (AEM) have the potential to dramatically improve the performance of electrolyzers in the near future. For the somewhat longer term it remains to be seen what intensification techniques will bring the next step in performance. If you are an engineer or practically oriented scientist with affinity with fluid mechanics, electrochemistry, and renewable energy, your help is needed to realize this next step in innovation.

The greatest challenge in the energy transition as a whole is the stability and reliability of the energy grid. To create a stable grid we need holistic insights, for which the data from energy markets, the control domain, and power and energy systems must be integrated. This is why Delft AI Energy Lab and the Vienna-based Austrian Institute of Technology have launched the joint ‘AI research in energy system planning and operations’ programme. As a postdoc, you will get the unique opportunity to develop your own vision and research line within the scope of the programme, in collaboration with our academic staff.

The Intelligent Electrical Power Grids (IEPG) research section has a very ambitious and diversified research programme covering major technological challenges concerning the operation and planning of future electrical sustainable electrical power grids.

The research team Resilient Sustainable Energy Systems of IEPG, led by Dr. Jose Rueda,  seeks a postdoctoral fellow, each one to research and develop modular and scalable digital twins for electromagnetic transient and real-time based assessment and enhancement of stability phenomena, focusing on poorly damped electrical oscillations with time-varying properties that can result in unstable multi-converter dynamic interplay.

The Intelligent Electrical Power Grids (IEPG) research section has a very ambitious and diversified research programme covering major technological challenges concerning the operation and planning of future electrical sustainable electrical power grids.

The research team Resilient Sustainable Energy Systems of IEPG, led by Dr. Jose Rueda, seeks a postdoctoral fellow to perform ground breaking research on adaptive management and coordination of primary and secondary supplementary control of power electronic converters to safeguard resiliency (dynamic stability and reliability) in highly variable operating conditions and random disturbances.

The Cybersecurity (CYS) group at the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) invites applications for full-time doctoral candidates in the area of Data-driven Cybersecurity. Successful candidates will follow a data-driven approach by collecting and analyzing massive network and web data to improve security and privacy in the Internet. Examples include fighting cyber threats (e.g., ransomware, phishing, denial of service attacks, scanning for system vulnerabilities), identifying and mitigating network and Web vulnerabilities (e.g., unauthorized access, user tracking), and assessing the adoption of user data protection regulations (e.g., GDPR) in the wild. Successful candidates will have the opportunity to work closely with world-class researchers at TU Delft and our research collaborators in Europe and the US.

 

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: Postdoc Hydrological Data Assimilation

Deadline : 30 May 2023

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The overarching aim of this project is to address these issues through a comprehensive simulation study, complemented by laboratory experiments carried out in a collaborative project, to characterise the key characteristics of depleted gas reservoirs that are suitable candidates for UHS. To achieve this aim, the successful candidate will be designing multi-scale reservoir modelling and simulation studies and utilise the results to develop dimensionless numbers that allow us to quantify the amount of back-produced hydrogen from depleted gas reservoirs while accounting for geological heterogeneity, mixing of cushion gas and hydrogen, geochemical reactions, and well designs.

Increasing housing density and decreasing space for transport infrastructure and private parking are threatening the sustainable accessibility of urban regions. Potential smart mobility solutions consist of flexible combinations of walking and cycling, shared electric vehicles, transport hubs, freight delivery and traffic management – but we lack the modelling tools to test these solutions.

In the XCARCITY Project we will develop realistic digital replicas of car-low areas in Amsterdam, Almere Pampus and the Metropolitan Region Rotterdam-The Hague. We will use these ‘digital twins’ to study how people use different smart mobility services. This will help cities, area developers and mobility providers to make informed decisions about smart mobility, ensuring that the car-low urban regions of the future remain accessible.

As a postdoc at TU Delft within the DBI2 program, you will build neuronal network models to enhance our understanding of the closed-loop interactions within the brain. You will validate your findings and explain experimentally found properties of brain networks. You will use your findings to refine our 4D-EEG methodology, which enables quantifying signal propagation through the brain. Moreover, you will closely work with a PhD student within the team and collaborate with partners within the consortium to use your knowledge and 4D-EEG methodology to enhance our understanding of behaviour and neurological diseases. The highly interdisciplinary work requires you to actively build bridges between system identification, control engineering, signal analysis and neurosciences.

We are looking for a talented, motivated and outstanding candidate with a PhD degree (or close to completion) in Technical Medicine, BioMedical Engineering, Physics, Electrical Engineering, Computer Science, Probabilistic Machine Learning, Computer Vision or a related field. The candidate should demonstrate a strong background and/or interest in the fields of Data Science and Machine Learning and affinity with the topic of Medical Workflow Optimization using Artificial Intelligence. The candidate must be enthusiastic and greatly interested in fundamental research in addition to having good programming skills, e.g., in Matlab or Python, for implementing state-of-the-art advanced algorithms. Furthermore, excellent written and oral communication skills in English, affinity with teaching and guiding students and the ability to work in a team and taking initiative are important for this position. Mastering the Dutch language is a pre.

In Hi-Drive, TU Delft focusses on human factors and is recruiting a post-doc or researcher in motion comfort. The candidate will investigate perceived motion comfort and motion sickness in particular when performing non-driving related tasks in automated vehicles. Here our key scientific challenge is to unravel processes leading to the perception of comfort and discomfort, and to translate these insight into models predicting comfort in automated driving.

The project will focus on handling statistical inverse problems with non-Gaussian priors. Gaussian process priors are often used in practice due to their fast computational properties. However, the smoothness of the resulting estimates is not well suited for modelling functions with sharp changes, met for ecample in imaging. As an alternative for Gaussian priors one can consider Besov priors that are well suited for producing piecewise smooth reconstructions and for edge and interface detection.

SoBigData++ is a distributed, multi-disciplinary research infrastructure for big social data analytics, coupled with the consolidation of a cross-disciplinary European research community, aimed at using social mining and big data to understand the complexity of our contemporary, globally-interconnected society. SoBigData++ develops applications that operationalize ethics with value-sensitive design, incorporating values and norms for privacy protection, fairness, transparency, and pluralism. SoBigData++ offers 91 unique datasets, 120 pilot projects developed with diverse companies, over 90 social mining methods, and apps, and more than 7,000 active users. In 2022, SoBigData entered the ESFRI Roadmap as SoBigData-RI (http://sobigdata.eu/index) with the purpose of offering their services (infrastructure, data, expertise) to state members. In the Netherlands, we intend to create the Dutch Research Node (DRN) that will bridge organizations, institutions, and government agencies with the services provided by SoBigData-RI. This postdoc project is a unique opportunity to assist in the creation of the DRN, engage with diverse stakeholders (from university academics to government officials), and take part in science and philosophy communication. This postdoc also includes the opportunity to advance in an academic position via teaching duties, research, and organization of events, as well as acquire experience in ethics consulting. The successful candidate will be affiliated with TU Delft and be part of a vibrant research community that includes the Delft Digital Ethics Centre, Delft Design for Values, and Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI).

The research is part of the Sustainable Dykes project, financed by NWO, and will be developed in strict cooperation with an ongoing PhD. The successful candidate will develop a numerical model integrating laboratory measurements and field observations in a multiphysics platform, able to provide a digital replica of typical Dutch regional dykes, which are being monitored for water content changes and deformations. Eventually, the digital twin will be used to assess the structural health of the dykes and design mitigation measures to reduce the impact of climate changes. The Thermo-Hydro-Mechanical numerical model will include proper constitutive models for the unsaturated and cyclic response of typical Dutch soft soils, and will be built on an advanced approach for the description of the soil-vegetation-atmosphere interaction.

In this 2-year project, you will review the currently available modeling and simulation efforts for allogeneic cell therapy production processes. This will form the basis of novel process designs, process simulations, and comparison studies of different technologies for transfection/transduction, expansion, and separation technology. The assessment of different technologies will be done in combination with an gap assesment for process analytical technology (PAT) to faciliate future automated monitoring and control.