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

Optical nanoscopy is a super-resolution microscopy technique to study subcellular structures and function via specifically targeted fluorescent labels in molecular biology. Localisation microscopy in particular offers a much better resolution (~10-50 nm) than conventional diffraction limited microscopy (~250 nm). This project aims at shifting the resolution obtainable in an optical light microscope even further towards 1 nm. 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.

Optical nanoscopy is a super-resolution microscopy technique to study subcellular structures and function via specifically targeted fluorescent labels in molecular biology. Localisation microscopy in particular offers a much better resolution (~10-50 nm) than conventional diffraction limited microscopy (~250 nm). This project aims at shifting the resolution obtainable in an optical light microscope even further towards 1 nm. 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. 

Are you a postdoc candidate with a fundamental interest in Synthetic Biology and Synthetic Genomics? Do you have a background in microbiology, molecular biology or biochemistry? Would you like to work together in a nation-wide multi-disciplinary team of researchers? We have a vacancy for a postdoc position focusing on harnessing the awesome homologous recombination of yeast for the construction of Synthetic Cells. You will be part of the nation-wide NWO Gravitation project BaSyC (https://www.basyc.nl/), aiming at constructing synthetic cells from lifeless component. At the interface of yeast and bacterial synthetic biology, you will work in close collaboration with the groups of Dr. Nico Claassens and Prof. John van der Oost from Wageningen University. In this project you will investigate the potential of the yeast Saccharomyces cerevisiae to construct Synthetic Genomes for Synthetic Cells.

The Intelligent Vehicles group and the Delft Center for Systems and Control (DCSC) at TU Delft are seeking a PostDoc interested in conducting fundamental research on Tensor Decomposition for efficient Deep Learning. As neural networks grow in size and power, reducing inference time without sacrificing accuracy is crucial for real-world applications like self-driving vehicles. Tensor decomposition has emerged as a promising technique for neural network compression. By breaking down high-dimensional weight tensors into lower-rank tensors, it compresses the model by reducing the number of parameters. Similarly, current research on sparcification of neural networks focuses on efficient sparsity-inducing methods such as structured sparsity patterns, channel pruning, and group sparsity. These methods aim for higher compression ratios while minimizing the impact on accuracy and performance. However, the connection between tensor decomposition and sparcification, both aiming for neural network compression, remains understudied.

Society puts ever increasing demands on coatings and paints, from aerospace structures where durable coatings reduce the need for aircraft repair, to civil infrastructure where new generation wood coatings are required to promote wood as a low-carbon, fully renewable construction material. However, the development of durable coatings is challenging for two main reasons: (i) Prolonged durability assessment as a result of sub-optimal inspection methods; (ii) Lack of understanding and insight into the microstructural properties of coatings both before and after aging processes. To address these challenges, we aim at using Atomic Force Microscopy (AFM) measurements with data-driven nonlinear dynamic methodologies to characterize viscoelastic proerpties. Our approach will go beyond ad hoc models that otherwise are used in viscoelastic characterizations and makes systematic use of machine learning to distil dissipative forces directly from AFM data over a range of frequencies, thus extracting high spatial and temporal information from the sample. By performing experiments on thin coating films under repetitive strain and different weathering conditions, we aim at tracing nanomechanical properties as a function of strain to underpin nanoscale properties that are accountable for the mechanical failure of these materials. The vacant position is in the Dynamics of Micro and Nanosystems (DMN) group. The group focuses on exploiting dynamics of small scale systems to create technologies that can lead to new products in the fields of scientific instrumentation, consumer electronics and healthcare. Our research spans from measuring and manipulating materials at the micro and nano scale, to the design of world-class  MEMS and NEMS sensors and actuators.

A 2-year post-doctoral position is open at Delft University of Technology in the Netherlands, in the department of Imaging Physics. Unlike common belief, we recently demonstrated that ultrasound can image the cortex of long bones and can measure pulsatile blood flow inside cortical bone tissue (https://doi.org/10.1002/jbm4.10543). This international project also involves the Laboratoire d’Imagerie Biomédicale at Sorbonne Université in Paris, France and Erasmus Medical Center in Rotterdam, the Netherlands.

Risk and resilience are two carriers of safety. They are often used to support design and opertional decisions in engineering. In this project, we aim to develop innovative resilience-based approach for maintenance and design of offshore systems, with a particular focus on naval ships. Naval vessels are valuable national assets. They are expensive to build and maintain, leading to many navies to seek to extend service-life and maximize operability using improved environmental sensing and planned maintenance intervals. The scientific contribution of this project aims to develop resilience modeling method and use it to support decision-making in asset integrity management using smart onboarding sensing. This Postdoc position is expected to conduct research on the above topic. Since this project is part of a NWO granted project, titled FUSION. The Postdoc fellow is also expected to work together with other researchers in this project to develop ecoomomic and safety analysis relating vessel performance metrics to proposed actions and cost/risk of delay. 

De uitdagingen in de gebouwde omgeving zoals de bouwproductie, klimaatadaptatie en circulariteit vragen om innovatie. Start-ups en scale-ups spelen hierin een belangrijke rol. Wat is er nodig om start-ups en scale-ups succesvol te laten zijn? Welke bijdrage kunnen (publieke) opdrachtgevers daaraan leveren? De kennis over wat start-ups succesvol maakt en hun ontwikkeling is nog beperkt. Als Postdoc bij de leerstoelen Construction Management en Entrepreneurship en Publiek Opdrachtgeverschap breng je in kaart wat de rol van start-ups en scale-ups is bij innovatie, wat de kenmerken zijn van en succesfactoren zijn voor de ontwikkeling van start-ups en hoe (publieke) opdrachtgevers het ontstaan en de doorontwikkeling van start-ups kunnen bevorderen. Hoe kan de deelname van start-ups aan samenwerkingsverbanden en aanbestedingen worden gestimuleerd en wat is er nodig voor een scale-up? Dat zijn de vragen waarnaar de Postdoc start-ups en scale-ups in de bouw kijkt. Je sluit aan bij de  onderzoeksactiviteiten van beide leerstoelen en kunt daarop voortbouwen.

The Garbin lab (https://garbinlab.org/) is looking for a postdoc with a strong background in physical acoustics and an interest in developing novel acoustofluidic methods for manipulation of soft matter. The project focuses on manipulation and sorting of soft particles for different applications. For instance, recently we have demonstrated enhanced cell wall permeability in microalgal cells using microbubble streaming flow (https://arxiv.org/abs/2112.08519) with reduced energy cost compared to conventional separations. You will join a diverse and interdisciplinary team working on microscale transport phenomena in soft and biological matter and you will have the opportunity to contribute to different ongoing projects.The Garbin lab is embedded in the Transport Phenomana section of the Department of Chemical Engineering, and the project offers exciting synergies with colleagues in the Department of Imaging Physics, and with an international network of collaborators.  

The Post Doc researcher will be part of the Design, Organization and Strategy (DOS) Department at the Industrial Design Engineering Faculty. DOS focuses on the strategic role of design in organisations with the intention to improve and renew the organisations’ strategies and thereby concurrently co-create value for individuals, organisations, and society at large. He/she will be supervised by Dr. Giulia Calabretta (DOS) and Prof. Paul Hekkert (Human-Centered Design Department). He/she will also be frequently interacting with the lively, international, and diverse Ekip consortium, predominantly University of Edinburgh and Politecnico di Milano. Some Ekip partners will be involved in the research design and some others will support the Post Doc in the data collection. The preferred start date for the position is Fall 2023, for a duration of 3 years (full time).

Within the COCOLIH2T project, funded by the Clean Hydrogen Joint Undertaking, we are collaborating with nine other partners to develop a conformal liquid hydrogen tank for aviation. In this position you will conduct safety and fatigue analyses of the developed tank design. Challenges include analysing the safety requirements and characteristics of the tank in the design stage, conducting fatigue analyses taking into account the complex thermomechanical loading, and coming up with a fatigue management concept for the tank, e.g. should it be based on safety-by-replacement or safety-by-inspection. To inform these analyses you will colloaborate with colleagues at TU Delft, as well as with project partners, working on the tank design, NDT, and life cycle analyses. In addition to conducting the research, you will be required to communicate it both in academic settings (journal papers and conferences) and towards an industrial audience. You will also be expected to contribute to the management of the project.

Life cycle evaluation is an important aspect of novel structures and needs to become an integral part of design. As such, the life cycle evaluation of composite pressure vessels, which may be used as storage tank for LH₂ in future airplanes, is an important aspect to investigate. In this work, two aspects of life cycle evaluation will be investigated to determine whether thermoset or thermoplastic composite materials are the best to use. On one hand, the manufacturing process itself will be studied, on the other hand the additional design options (and possible weight savings) when using thermoplastic material rather than thermoset will be investigated. By the end of the project, an informed decision about the best option shall be presented. This position is part of the COCOLIGH2T (COmposite COnformal Liquid H₂ Tank) project. In this project the main aim is to design, develop, and manufacture a disruptive, safe, and lightweight LH₂ storage system for the aviation sector with increased volumetric efficiency. This storage system will be conformal and made out of composite material.

Automated Fibre Placement (AFP) is one of the methods currently used to produce composite structures in an automated fashion. When using thermoplastic materials, in-situ consolidation can be achieved when using a laser as a heating source. However, lasers are a big investment and comes with safety concerns. An alternative heating method, using pulsed light, has been developed recently. The advantages are that the safety concerns are not as high and would thus allow easier implementation in an industrial environment, while it delivers highly controllable heat to the process area. The goal of this project is to investigate the possibilities of using pulsed light as an alternative heat source to achieve in-situ consolidation for thermoplastic composite material in automated fibre placement. The research will be conducted at SAM XL (SAMXL): they will take care of the integration of the heating system on their robot, but the correct operation and manufacturing parameters definition is to be investigated within this project. The technology evaluation should include (but is not limited to) microstructural characterisation, structural characterisation and determining bounds on the manufacturing parameters used during automated fibre placement (i.e., manufacturing envelope). For this research the HUMM3 heating system will be utilized. You will spend time both at the faculty of aeropace engineering and SAM XL.

AiDAPT Lab, TU Delft’s Artificial Intelligence Lab for Design, Analysis, and Optimization in Architecture & Built Environment, invites applications for one Postdoc position in the interdisciplinary domain of deep learning for building energy retrofit planning. The abundance of data and the ever-increasing computing power enables us to scale up the analysis of buildings at different data layers and scales. We are looking for candidates highly motivated to work at the confluence of data science, computer vision, and building technology to address the energy transition needs of our aging and growing buildings at the urban scale. The candidate will work on the development of novel datasets and computer vision deep learning architectures that enable us to support building intervention decisions, with an emphasis on cities in the Netherlands and Rotterdam in particular. This research will produce new databases of visual data and baseline computer vision models that advance our capabilities to streamline retrofit resources for real-world buildings. The research will further seek to couple imagery data with other types of climate, building performance, and social data for the training and evaluation of deep learning models towards automatic analysis of diverse building stocks.  This postdoctoral research is linked to the DE-CIST project, funded by a granting scheme conducted by Google to foster data-driven environmental and climate action at the local level. The project’s goal is to develop scalable, transferable, and automated data-driven methods, able to bolster energy transition through optimal retrofit planning in the city of Rotterdam.

 

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: Postdoc for generation of Orbital Angular Momentum using Artificial Intelligence for Quantum OCT

Deadline :5 July 2023

View details & Apply

 

We are seeking a postdoctoral researcher for an 18-month contract to develop coupled musculoskeletal and hydrodynamic models, perform novel simulations and collect experimental data to identify model parameters and to test model accuracy. We aim to develop a rowing simulation environment that enables us to refine oar, blade and oarlock design and adjust athlete technique to maximize efficiency at high speeds. Your project is supported by a Cohesion grant between the departments of Biomechanical Engineering and Process & Energy at TU Delft. You will simultaneously work as a member of the Computational Biomechanics Lab and the Fluid Mechanics Lab under the guidance of Ajay Seth and Arnoud Greidanus, respectively. The work within this program is multi-disciplinary and involves computational modeling and experimental research with support of specialists (scientific/non-scientific). An extensive lab equipped with state-of-the-art facilities and equipment are widely available for the experimental work.

Enabling machines to interpret social behaviour in real life is a major frontier of Modern Artificial Intelligence (AI). Unfortunately, there is almost no attention on developing systems to infer intentions. Those claiming to do so are labelling them by observing the future. This is problematic because they cannot detect unrealised intentions or unintended outcomes. Intention estimation is extremely challenging because inferences need to be explained with respect to situational context. This project develops a novel framework and learning approaches to learn narratives of intention from multiple perspectives in in-the-wild ecologically valid social situations such as social networking events.

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. You will fabricate and optimise the implants in the Class 100 cleanroom facility on the TU Delft campus. This part of the project will allow you to apply your expertise and further specialise in silicon-based microfabrication and polymer processing. Moreover, you will design and develop relevant characterisation set-ups and evaluate the electrochemical and stable performance of the implants in multimodal scenarios. Performance optimization and validation will present unique challenges at both system and device levels and require developing innovative designs alongside novel fabrication techniques and processes. Validation will be performed in vitro in-house, and in vivo in our collaborators’ laboratories, where you will work closely with other researchers (Postdocs and PhD candidates) with a neuroscience background. This part of the work will require that you work closely with them to translate in vivo testing specifications into system and device design solutions. The above activities and results will be published in collaborative discipline-specific and multidisciplinary journals, with you operating as a primary and co-first author.

This postdoctoral research position is part of a research project that aims to transform the aviation industry into a sustainable and clean sector. The BrightSky project, a Dutch collaboration where companies, educational institutions, and knowledge centres join forces to drive innovation and create a positive impact in many sectors at and around the airport, including the maintenance of aircraft. As a postdoctoral researcher within this project, you will be able to apply your modelling skills, knowledge of aircraft maintenance and operations, teamwork skills, and ability to generate ground-breaking research and innovation. Working closely with a dynamic team in a practical environment, you will be inspired by chance to collaborate directly with problem owners and research partners who have dedicated years to this research field.

Precision agriculture, which employs sensing technology and artificial intelligence to drive automated agriculture processes and decisions, has demonstrated great potential to improve efficiency, transparency, and productivity in the sector. For example, automated crop monitoring in greenhouses can be carried out collaboratively in real time using handheld devices and autonomous robots to collect data and monitor crop health. While AI has shown promise in many context-sensing tasks, realizing the full potential of AI for automated crop monitoring requires overcoming several research challenges. These include designing computationally efficient deep learning solutions for resource-constrained edge devices and addressing the sparse data problem in training robust monitoring systems.  To develop edge computing and AI-assisted solutions for resource-efficient and robust mobile crop monitoring, the Embedded System Group is offering a 4-year Ph.D. position funded by the Dutch National Growth Fund NXTGEN Hightech program. We are seeking a highly qualified candidate to work on this challenging but impactful project. The candidate will be supervised by Dr. Guohao Lan and Prof. dr. Koen Langendoen and collaborate with the TU Delft AgTech Institute and our industry collaborator Sobolt