Director of the School of the Biological Sciences Microscopy Bioscience Platform (Associate Research Professor (G10)/Research Professor (G11))
We are seeking a new Director for the Microscopy Bioscience Platform (https://www.bio.cam.ac.uk/microscopy-platform), based within the School of the Biological Sciences city centre campus. This strategically important position will manage, develop and inspire an established team that delivers cutting-edge approaches and supports more routine imaging techniques. Through wide-ranging collaborations with our world-leading scientists, who use microscopy in a huge range of modalities and subject areas, the chosen candidate will have unique opportunities to foster research that contributes to our reputation as a global centre of biological sciences research. In addition to the knowledge and skills to drive innovation and support our world-leading research the successful candidate will have proven leadership skills and demonstratable experience in people and facility management. Building on a foundation of innovative microscopy, the Microscopy Bioscience Platform was successfully launched in 2024 and has received substantial investment in staff and instrumentation from both internal and external funders (including successful bids to UKRI equipment calls). The role holder will capitalise on this existing commitment, ensuring that the Platform is at the forefront of microscopy and that it is accessed by a diverse portfolio of academic, industry and commercial users to secure financial sustainability. To achieve this, they will establish and maintain wide-ranging contacts across the user groups, to be familiar with their needs and future plans, as well as networking with the national and international microscopy community to keep at the forefront of the field and seize opportunities for partnerships. There would also be the opportunity to embed a research group funded from external grant applications for those who wished to further advance a relevant field. Appointment at the Associate Research Professor (G10) or Research Professor (G11) level will be dependent on experience. For Grade 11 evidence of strategic leadership, responsibility for major research programmes, management of major budgets and resources, leadership of external networks, and a broader impact through consultancy and commercial activities would be expected. The Microscopy Bioscience Platform The Microscopy Bioscience Platform is an initiative to provide a focus for microscopy support and development across seven Departments in the School of the Biological Sciences. The primary aim of the Platform is to foster innovation and collaboration, offering supported access to a wide array of advanced instruments and a focal point for technology development in the biological sciences, delivered via the Cambridge Advanced Imaging Centre (CAIC) and externally funded research grants. Across light, advanced and electron microscopy, the Platform has a substantial user group of over 180 research groups and commercial companies. The Platform operates across an extremely diverse range of science, encompassing a wide breadth of organisms and microscopy modalities. This diversity requires an agile response, based on the experience and skills of senior team members, and an excellent instrument portfolio that has been subject to significant investment from both internal and external sources of funding. This is in addition to CAIC's bespoke microscope construction that enables both development of new research approaches and technical translation to commercial applications. In fulfilling their role, the Director will be guided by an established strategic board, and their post will be managed by the Head of the Department of Physiology, Development and Neuroscience. For more information about the role and list of essential skills and experience, please refer to the Further Particulars. Informal enquiries about the position can be made to Professor Sarah Bray sjb32@cam.ac.uk or Dr Ben Steventon bjs57@cam.ac.uk. Apply: Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online. Applications should consist of a letter of application, a research and operational vision for developing the Microscopy Bioscience Platform (2 pages maximum) and a curriculum vitae. The full contact details for three professional referees should be provided. Please note that we will assume that you are happy for us to approach your referees at any stage, unless you indicate otherwise in the space provided on the form. The closing date for applications is 11 October 2026. Interviews are expected to be held in November. Please quote reference PM51041 on your application and in any correspondence about this vacancy. The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
E11 Bio - Scientist/Senior Scientist, Molecular Engineering & Sample Optimization
E11 Bio is recruiting an experimental scientist to advance scalable mammalian brain connectomics. The role integrates tissue preparation, microscopy, quantitative analysis, and molecular engineering across reagent panels for comprehensive synapse identification and barcode-epitope readout.
Scaling Up Bioimaging with Microfluidic Chips
Explore how microfluidic chips can enhance your imaging experiments by increasing control, throughput, or flexibility. In this remote, personalized workshop, participants will receive expert guidance, support and chips to run tests on their own microscopes.
“A Focus on 3D Printed Lenses: Rapid prototyping, low-cost microscopy and enhanced imaging for the life sciences”
High-quality glass lenses are commonplace in the design of optical instrumentation used across the biosciences. However, research-grade glass lenses are often costly, delicate and, depending on the prescription, can involve intricate and lengthy manufacturing - even more so in bioimaging applications. This seminar will outline 3D printing as a viable low-cost alternative for the manufacture of high-performance optical elements, where I will also discuss the creation of the world’s first fully 3D printed microscope and other implementations of 3D printed lenses. Our 3D printed lenses were generated using consumer-grade 3D printers and pose a 225x materials cost-saving compared to glass optics. Moreover, they can be produced in any lab or home environment and offer great potential for education and outreach. Following performance validation, our 3D printed optics were implemented in the production of a fully 3D printed microscope and demonstrated in histological imaging applications. We also applied low-cost fabrication methods to exotic lens geometries to enhance resolution and contrast across spatial scales and reveal new biological structures. Across these applications, our findings showed that 3D printed lenses are a viable substitute for commercial glass lenses, with the advantage of being relatively low-cost, accessible, and suitable for use in optical instruments. Combining 3D printed lenses with open-source 3D printed microscope chassis designs opens the doors for low-cost applications for rapid prototyping, low-resource field diagnostics, and the creation of cheap educational tools.
Optogenetic control of Nodal signaling patterns
Embryos issue instructions to their cells in the form of patterns of signaling activity. Within these patterns, the distribution of signaling in time and space directs the fate of embryonic cells. Tools to perturb developmental signaling with high resolution in space and time can help reveal how these patterns are decoded to make appropriate fate decisions. In this talk, I will present new optogenetic reagents and an experimental pipeline for creating designer Nodal signaling patterns in live zebrafish embryos. Our improved optoNodal reagents eliminate dark activity and improve response kinetics, without sacrificing dynamic range. We adapted an ultra-widefield microscopy platform for parallel light patterning in up to 36 embryos and demonstrated precise spatial control over Nodal signaling activity and downstream gene expression. Using this system, we demonstrate that patterned Nodal activation can initiate specification and internalization movements of endodermal precursors. Further, we used patterned illumination to generate synthetic signaling patterns in Nodal signaling mutants, rescuing several characteristic developmental defects. This study establishes an experimental toolkit for systematic exploration of Nodal signaling patterns in live embryos.
From primate anatomy to human neuroimaging: insights into the circuits underlying psychiatric disease and neuromodulation; Large-scale imaging of neural circuits: towards a microscopic human connectome
On Thursday, October 26th, we will host Anastasia Yendiki and Suzanne Haber. Anastasia Yendiki, PhD, is an Associate Professor in Radiology at the Harvard Medical School and an Associate Investigator at the Massachusetts General Hospital and Athinoula A. Martinos Center. Suzanne Haber, PhD, is a Professor at the University of Rochester and runs a lab at McLean hospital at Harvard Medical School in Boston. She has received numerous awards for her work on neuroanatomy. Beside her scientific presentation, she will give us a glimpse at the “Person behind the science”. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!
Introducing YAPiC: An Open Source tool for biologists to perform complex image segmentation with deep learning
Robust detection of biological structures such as neuronal dendrites in brightfield micrographs, tumor tissue in histological slides, or pathological brain regions in MRI scans is a fundamental task in bio-image analysis. Detection of those structures requests complex decision making which is often impossible with current image analysis software, and therefore typically executed by humans in a tedious and time-consuming manual procedure. Supervised pixel classification based on Deep Convolutional Neural Networks (DNNs) is currently emerging as the most promising technique to solve such complex region detection tasks. Here, a self-learning artificial neural network is trained with a small set of manually annotated images to eventually identify the trained structures from large image data sets in a fully automated way. While supervised pixel classification based on faster machine learning algorithms like Random Forests are nowadays part of the standard toolbox of bio-image analysts (e.g. Ilastik), the currently emerging tools based on deep learning are still rarely used. There is also not much experience in the community how much training data has to be collected, to obtain a reasonable prediction result with deep learning based approaches. Our software YAPiC (Yet Another Pixel Classifier) provides an easy-to-use Python- and command line interface and is purely designed for intuitive pixel classification of multidimensional images with DNNs. With the aim to integrate well in the current open source ecosystem, YAPiC utilizes the Ilastik user interface in combination with a high performance GPU server for model training and prediction. Numerous research groups at our institute have already successfully applied YAPiC for a variety of tasks. From our experience, a surprisingly low amount of sparse label data is needed to train a sufficiently working classifier for typical bioimaging applications. Not least because of this, YAPiC has become the "standard weapon” for our core facility to detect objects in hard-to-segement images. We would like to present some use cases like cell classification in high content screening, tissue detection in histological slides, quantification of neural outgrowth in phase contrast time series, or actin filament detection in transmission electron microscopy.
OpenFlexure
OpenFlexure is a 3D printed flexure translation stage, developed by a group at the Bath University. The stage is capable of sub-micron-scale motion, with very small drift over time. Which makes it quite good, among other things, for time-lapse protocols that need to be done over days/weeks time, and under space restricted areas, such as fume hoods.
Imperial Neurotechnology 2021 - Annual Research Symposium
A diverse mix of neurotechnology talks from academic and industry colleagues plus presentations from our MRes Neurotechnology students. Visit our event page to find out more and register now!
BrainGlobe: a Python ecosystem for computational (neuro)anatomy
Neuroscientists routinely perform experiments aimed at recording or manipulating neural activity, uncovering physiological processes underlying brain function or elucidating aspects of brain anatomy. Understanding how the brain generates behaviour ultimately depends on merging the results of these experiments into a unified picture of brain anatomy and function. We present BrainGlobe, a new initiative aimed at developing common Python tools for computational neuroanatomy. These include cellfinder for fast, accurate cell detection in whole-brain microscopy images, brainreg for aligning images to a reference atlas, and brainrender for visualisation of anatomically registered data. These software packages are developed around the BrainGlobe Atlas API. This API provides a common Python interface to download and interact with reference brain atlases from multiple species (including human, mouse and larval zebrafish). This allows software to be developed agnostic to the atlas and species, increasing adoption and interoperability of software tools in neuroscience.
Non-Telecentric 2P microscopy for 3D random access mesoscale imaging
Ultra-low-cost, easily implemented and flexible two-photon scanning microscopy modification offering a several-fold expanded three-dimensional field of view that also maintains single-cell resolution. Application of our system for imaging neuronal activity has been demonstrated on mice, zebrafish and fruit flies. Website: https://github.com/BadenLab/nTCscope
An open-source experimental framework for automation of cell biology experiments
Modern biological methods often require a large number of experiments to be conducted. For example, dissecting molecular pathways involved in a variety of biological processes in neurons and non-excitable cells requires high-throughput compound library or RNAi screens. Another example requiring large datasets - modern data analysis methods such as deep learning. These have been successfully applied to a number of biological and medical questions. In this talk we will describe an open-source platform allowing such experiments to be automated. The platform consists of an XY stage, perfusion system and an epifluorescent microscope with autofocusing. It is extremely easy to build and can be used for different experimental paradigms, ranging from immunolabeling and routine characterisation of large numbers of cell lines to high-throughput imaging of fluorescent reporters.
Spinners, not swimmers: how sperm flagella fooled us for 350 years - now in 3D!
In the 17th century, Antonie van Leeuwenhoek used one of the earliest microscopes to see how sperm swim. He described the sperm as a “living animalcule” with a “tail, which, when swimming, lashes with a snakelike movement, like eels in water”. Strikingly, this perception of how sperm moves has not changed since. Indeed, anyone today with a modern microscope would make the same observation: sperm swim forward by wiggling their tail symmetrically side-to-side. Our new research using 3D microscopy shows that we have all been victims of a sperm deception, an illusion. Only now we can see that for 350 years we have been wrong about how sperm actually swims.