Federico Gasparoli

@fedegasparoli.bsky.social

Director of the Core for Imaging Technology & Education 🔬💻 Harvard Medical School

The Cimini lab is hiring for both postdocs and interns! The postdoc role will cover bioimage analysis projects and educational material creation; the intern will be working on our Bilayers project for helping distribute and access deep learning tools for bioimage analysis. Click below to learn more!

Postdoctoral Associate and Data Science Intern roles - Broad Institute, Cambridge MA USA

The Broad Institute Imaging Platform (the team behind CellProfiler, Piximi, and Bilayers) is currently hiring for postdoctoral and intern roles! Postdoc role: we are looking for 1-2 candidates who ha...

forum.image.sc

Want to apply to #BoBiAC2026 but need funding to attend? Thanks to support from @bioimagingna.bsky.social, we can provide a number of course fee waivers to accepted academic applicants who request one by completing the relevant section of the application form. More info: bobiac.github.io

BoBiAC 2026 | Boston Bioimage Analysis Course

A 6-day, beginner-friendly course covering Python-based bioimage analysis: segmentation, classification, colocalization, and more.

bobiac.github.io

My first corresponding author 🔬🎸🦾 rupress.org/jcb/article/... Ever wonder what the ultrastructure of dopaminergic neuron presynaptic sites looks like? Using cryo-CLEM/ET we observed the wild changes that happen at these sites when the neurons fire or are more quiet. In the latest @jcb.org

Ultrastructure of dopaminergic varicosities revealed by cryo-correlative light and electron microscopy

Lycas et al. develop a cryo-CLEM workflow to characterize the ultrastructure of dopaminergic varicosities. They resolve in situ structures of TRiC/CCT and

rupress.org

We opened 4 PhD positions at @humantechnopole.bsky.social together with Polimi (see 👇). My lab offers a PhD project on "Computational Morphogenesis": use state-of-the-art machine learning methods together with realistic simulations to build digital twins of developing tissue. Apply by March 26.

Human Technopole@humantechnopole.bsky.social · 6mo ago

🎓 How can #AI and #datascience unlock new insights into human health? 📊 We’re offering 4 #PhD positions through Polimi’s DADS Programme in the groups of Emanuele Di Angelantonio, Francesca Ieva, @janfunkey.bsky.social and Fernanda Pinheiro. Apply by 26 March 👉 humantechnopole.it/en/news/4-ph...

PAPER OUT ✨ How can we make smart microscopy more interoperable? What are the technical and cultural challenges? 30+ people from academia and industry propose a roadmap: doi.org/10.1515/mim-... Also a review of applications and repo of implementations. Join the discussion! smartmicroscopy.github.io

Screenshot of the abstract:
Smart microscopy is transforming life sciences by automating experimental imaging workflows and enabling real-time adaptation based on feedback from images and other data streams. This shift increases throughput, improves reproducibility, and expands the functional capabilities of microscopes. However, the current landscape is highly fragmented. Academic researchers often develop custom solutions for specific scientific needs, while industry offerings are typically proprietary and tied to specific hardware. This diversity, while fostering innovation, also creates major challenges in interoperability, reproducibility, and standardization, which slows progress and adaption. This article presents a collaborative effort between academic and industry leaders to survey the current state of smart microscopy, highlight representative implementations, and identify common technical and organizational barriers. We propose a framework for greater interoperability based on shared standards, modular software design, and community-driven development. Our goal is to support collaboration across the field and lay the groundwork for a more connected, reusable, and accessible smart microscopy ecosystem. We conclude with a call to action for researchers, hardware developers, and institutions to join in building an open, interoperable foundation that will unlock the full potential of smart microscopy in life science research.Screenshot of Figure 5: Interoperable smart microscopy ecosystem. Concept of a modular architecture for smart microscopy, where standardized experiment descriptions (e.g. useq-schema) and open data formats (e.g. OME-Zarr) allow integration of diverse microscopes, analysis tools, and user interfaces. Core components such as segmentation [76], [77], tracking [79], [80], and experiment logic are decoupled from specific hardware, enabling reuse across platforms. The system supports multiple input modalities (code, GUI, or natural language) and can be extended with additional devices like fluidics or environmental control modules. This structure enables flexible, feedback-driven acquisition strategies and cross-platform reproducibility.Screenshot of figure 4: Strategies for hardware abstraction that allow smart microscopy workflows to run across different microscope systems, illustrated with example implementations collected on the SMWG website. (A) Software communication layers: Image analysis and experiment logic are implemented in a platform-independent manner, while platform-specific adaptors control acquisition through proprietary microscope software via macros, APIs, or other interfaces. Custom GUIs allow users to configure analysis, while the vendor-provided software manages hardware and acquisition settings. By developing additional adaptors, these workflows can be extended to support microscope systems from other vendors. Example implementation: AutoMicTools , Supplementary Information S3. (B) Device-level standardization (e.g. μManager-based workflows) bypasses proprietary GUIs and provides a unified API for direct device control across manufacturers. This API abstracts vendor-specific differences, enabling consistent control of a growing collection of supported hardware. Example implementation: UU_smart_microscopy , Supplementary Information S2. (C) Event-based standardization decouples experimental design from hardware by describing acquisition events (e.g. acquire frame at x, y, t with channel c) in a structured format (e.g. useq-schema). Control software interprets these definitions and translates them into device-specific commands, enabling the use of vendor-specific features and optimizations during execution. Example implementation: rtm-pymmcore, Supplementary Information S1.
eurobioimaging.bsky.social@eurobioimaging.bsky.social · 6mo ago

🚨Publication! New review on #SmartMicroscopy: current implementations and a roadmap for interoperability by @lhinderling.bsky.social & colleagues from #EuroBioImaging's #SmartMicroscopy Working Group! 🔗 www.eurobioimaging.eu/news/new-pub... 📸 Hinderling et al, 2026, (DOI: 10.1515/mim-2025-0029)

Apply to join us this July for a crash course on Python & bioimage analysis tailored specifically for beginners! Applications due May 18th 🔬💻 #BoBiAC2026 bobiac.github.io

Federico Gasparoli@fedegasparoli.bsky.social · 7mo ago

📣 We are accepting applications for the 2026 Boston Bioimage Analysis Course (BoBiAC): bobiac.github.io! Join us this July at Harvard Medical School for a 6-day intensive hands-on course to learn bioimage analysis with Python! Apply by May 18th! No prior Python experience required! 🧫->🔬->💻->📊

Rewrote my Python bioformats wrapper (from aicsimageio/bioio) as a standalone package: - fully bootstrapped Java setup (just pip install) - lazy, repeatably-indexable Array object - fully spec-compliant OME-Zarr group obj. - xarray/dask exports github.com/imaging-form... v0.0.rc1 on PyPI

GitHub - imaging-formats/bffile: Modern Bio-Formats wrapper with clean lazy Python API

Modern Bio-Formats wrapper with clean lazy Python API - imaging-formats/bffile

github.com

📣 We are accepting applications for the 2026 Boston Bioimage Analysis Course (BoBiAC): bobiac.github.io! Join us this July at Harvard Medical School for a 6-day intensive hands-on course to learn bioimage analysis with Python! Apply by May 18th! No prior Python experience required! 🧫->🔬->💻->📊

Bild

Don't let the price of QI deter you! QI offers financial aid through NCI, HHMS, and @bioimagingna.bsky.social. Include a brief statement of need with your application. Aid is distributed by CSHL (not the course instructors). Many of our students - sometimes all! - receive significant support.

Join us at CSHL for Quantitative Imaging: From Acquisition to Analysis—two weeks of advanced imaging, analysis, and hands-on labs with cutting-edge microscopes and open source software! 📅 April 6–21, 2026 📝 Applications due Friday Jan 30, 2026

🔬 🖥️ Applications are open for the CSHL course Quantitative Imaging: From Acquisition to Analysis (April 6–21, 2026)! An intensive, hands-on course covering advanced fluorescence microscopy and quantitative image analysis using open-source tools. 🗓️ Apply online by Jan 30, 2026

Quantitative Imaging: From Acquisition to Analysis

Cold Spring Harbor Laboratory Meetings & Courses -- a private, non-profit institution with research programs in cancer, neuroscience, plant biology, genomics, bioinformatics.

meetings.cshl.edu

Just 4 days until the start of I2K and its 33 totally free image analysis tutorials and events! Please share with your "home networks", especially early career researchers - the videos will be amazing and high-impact no matter how many people attend live, BUT (1/x)

A fluorescent embryo on black text, with the words 
Halfway to I2K: Virtual Tutorials on Image Analysis
November 17-19, 2025
Virtual Conference for beginners to developers
i2kconference.org
Image Credit - "Sweet Embryo",Travis D. Carney, BINA Image Contest 2024