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Federico Gasparoli

@fedegasparoli.bsky.social
732 followers 96 following 3 posts

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

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Reposted by Federico Gasparoli
Eva de la Serna @sciencedoodles.bsky.social · 09/07/2026
Thanks to generous funding from @bioimagingna.bsky.social, We were able to offer nearly half of our #BoBiAC2026 students fee waivers so that they could attend the course! The students also got to hear more about BINA programming & resources during a guest presentation from BINA 🔬
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Federico Gasparoli @fedegasparoli.bsky.social · 13/05/2026
Few days left to apply!!!👇#BoBiAC
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Beth Cimini 🔬💻📊 @bethcimini.bsky.social · 07/05/2026
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!
forum.image.sc
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...
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Damian Dalle Nogare @damiandn.bsky.social · 11/05/2026
Last week to apply! 👇🏻👇🏻👇🏻 (Closes Friday)
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Eva de la Serna @sciencedoodles.bsky.social · 04/05/2026
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.github.io
BoBiAC 2026 | Boston Bioimage Analysis Course
A 6-day, beginner-friendly course covering Python-based bioimage analysis: segmentation, classification, colocalization, and more.
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Eva de la Serna @sciencedoodles.bsky.social · 04/05/2026
2 wks left to apply to join #BoBiAC2026! This course will teach you how to use Python to segment fluorescence images w/tools like @ilastik-team.bsky.social & CellposeSAM, & even how to measure cell features, neighborhood relationships, & colocalization. No coding experience needed! bobiac.github.io
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Matt Lycas @lycasworks.bsky.social · 04/05/2026
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
rupress.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
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QI@CSHL @qiatcshl.bsky.social · 11/04/2026
We tried other brands but nothing works quite like a Guinness for our light sheet microscope. Future collab?
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QI@CSHL @qiatcshl.bsky.social · 10/04/2026
Today Hunter Elliott is lecturing on image processing. Key take-home before lunch: There is no free lunch:)
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Florian Jug @florianjug.bsky.social · 02/04/2026
We've spent the last year building something at @humantechnopole.bsky.social that we think is genuinely needed: #AI that works across biological scales and data modalities, not just within them. A thread on what we're doing, why, and who we're looking for. A 🧵... 1/9
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Jan Funke @janfunkey.bsky.social · 05/03/2026
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.
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Lucien Hinderling @lhinderling.bsky.social · 03/03/2026
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.
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Eva de la Serna @sciencedoodles.bsky.social · 03/03/2026
Apply to join #BoBiAC2026 this summer! You'll learn how to use Python to segment fluorescence images w/tools like @ilastik-team.bsky.social & CellposeSAM, & even learn how to measure cell features, neighborhood relationships, & colocalization. No coding experience needed! More info: bobiac.github.io
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Eva de la Serna @sciencedoodles.bsky.social · 03/02/2026
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
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Talley Lambert @talley.codes · 16/02/2026
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.com
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
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Federico Gasparoli @fedegasparoli.bsky.social · 03/02/2026
📣 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! 🧫->🔬->💻->📊
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QI@CSHL @qiatcshl.bsky.social · 28/01/2026
Applications for QI 2026 are due on Friday! 🔬 🖥️ 📊 😺
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QI@CSHL @qiatcshl.bsky.social · 28/01/2026
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.
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QI@CSHL @qiatcshl.bsky.social · 28/01/2026
🔬 🖥️ 📊!
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Jennifer Waters @jencwaters.bsky.social · 28/01/2026
QI Class of 2025! Centroid = @sciencedoodles.bsky.social & @florianjug.bsky.social / first minima = @talley.codes & me. Applications for 2026 due on Friday! meetings.cshl.edu/courses.aspx...
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Jennifer Waters @jencwaters.bsky.social · 27/01/2026
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
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Florian Jug @florianjug.bsky.social · 21/01/2026
🚨 Only a few days left to apply for maybe the best microscopy course there is!!! 🚨 👇👇👇👇👇👇👇👇👇👇👇
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Damian Dalle Nogare @damiandn.bsky.social · 22/01/2026
Re-upping: if you want to learn microscopy and image analysis - REALLY learn them, in an intense and hands on way - this is a really great place to do it. Applications close Jan 30 meetings.cshl.edu/courses.aspx...
meetings.cshl.edu
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.
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Matt Lycas @lycasworks.bsky.social · 20/01/2026
🔬🚨New preprint alert! 🚨🔬 We developed quantitative expansion microscopy (qExM) - a method to accurately count proteins in situ by combining expansion microscopy's improved labeling with statistical estimators borrowed from ecology www.biorxiv.org/content/10.6... #SuperResolution #CellBiology
biorxiv.org
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Damian Dalle Nogare @damiandn.bsky.social · 09/01/2026
Want to up your microscopy and image analysis game? Applications open now for QI 2026! Join us in cold spring harbor for two weeks of intensive training in all things microscopy.
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Jennifer Waters @jencwaters.bsky.social · 06/01/2026
🔬 🖥️ 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
meetings.cshl.edu
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.
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Beth Cimini 🔬💻📊 @bethcimini.bsky.social · 13/11/2025
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
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Lucien Hinderling @lhinderling.bsky.social · 21/08/2025
🔬🧠 Our paper on smart microscopy & the issue of interoperability! www.biorxiv.org/content/10.1... LONG THREAD WARNING: Smart microscopy uses real-time image analysis to automatically guide the acquisition or perturbation of the sample (closed feedback-control loop). Many applications exist:
Figure legend: Categories and capabilities of smart microscopy systems integrating real-time image analysis and feedback control. Top: Smart microscopy workflows can be classified based on the driving logic behind decision-making: Event-driven (reacting to rare biological events), Outcome-driven (using feedback-control to steer biological systems toward a desired state), Quality-driven (optimizing signal quality or imaging metrics), and Information-driven (guided by models that predict which measurements/perturbations will yield the most informative data). Middle: Central feedback loop between the microscope and an image analysis system, which continuously
exchanges images and commands to guide acquisition dynamically. Bottom: Key control actions enabled by smart microscopy: adjusting imaging modality (e.g. switching from brightfield to fluorescence, adjusting sampling rate), repositioning the field of view (e.g. tracking, drift correction), optimizing acquisition settings (e.g. adaptive optics),
and performing photomanipulation (e.g. FRAP, ablation, optogenetics).
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Eva de la Serna @sciencedoodles.bsky.social · 29/07/2025
Check out our amazing #bobiac2025 cohort! Was a joy to teach this group! Thanks @bioimagingna.bsky.social for generously supporting this 6 week bioimage analysis w/Python course!
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HMS Image Analysis Collaboratory @hms-iac.bsky.social · 14/07/2025
Day 1 of #bobiac2025 🐍 The day started strong with @talley.codes speaking about the Python ecosystem and uv. Students then gave short talks about their research (#coolscience). It was then time to code in Python with @sciencedoodles.bsky.social!
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HMS Image Analysis Collaboratory @hms-iac.bsky.social · 30/05/2025
‼️3 days left to apply to the Boston Bioimage Analysis Course (BoBiAC)! 💻 Get started w/Python & learn to analyze fluorescence microscopy images — no programming experience required! Fee waivers available! 🗓️ Apply by June 1st! 🌐 iac.hms.harvard.edu/bobiac/2025/
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Talley Lambert @talley.codes · 21/05/2025
for you other colorblind coders out there, tired of missing the red X in your github actions logs .color-fg-danger, .fgColor-danger {color: magenta !important;} .octicon-x {color: magenta !important;} you're welcome
custom github css
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HMS Image Analysis Collaboratory @hms-iac.bsky.social · 08/05/2025
💻 Apply to our beginner-friendly Boston Bioimage Analysis Course! Get started with Python and learn to analyze fluorescence microscopy images — no coding experience required! Fee waivers available thanks to funding from @bioimagingna.bsky.social! 🗓️ Apply June 1st! iac.hms.harvard.edu/bobiac/2025/
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HMS Image Analysis Collaboratory @hms-iac.bsky.social · 07/05/2025
We are proudly hosting 𝐃𝐫. 𝐓𝐚𝐥𝐥𝐞𝐲 𝐋𝐚𝐦𝐛𝐞𝐫𝐭 @talley.codes (CITE, Harvard Medical School): 𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐧𝐠 𝐫𝐞𝐚𝐥𝐢𝐬𝐭𝐢𝐜 𝐥𝐢𝐠𝐡𝐭 𝐦𝐢𝐜𝐫𝐨𝐬𝐜𝐨𝐩𝐲 𝐢𝐦𝐚𝐠𝐞𝐬 𝐮𝐬𝐢𝐧𝐠 𝐦𝐢𝐜𝐫𝐨𝐬𝐢𝐦 When: 𝐌𝐚𝐲 𝟐𝟗𝐭𝐡 @ 𝟏𝟏 𝐚𝐦 𝐄𝐃𝐓 (Boston time) Join us on Zoom! harvard.zoom.us/j/9762343464...
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Beth Cimini 🔬💻📊 @bethcimini.bsky.social · 01/05/2025
BIG NEWS - for the first time ever, we're running a Bioimage Analysis Beginnings Bootcamp. Learn #bioimageanalysis from awesome folks, and gain familiarity with some new tools as well as how to pick the right tool in the first place. Aug 4th-8th - apply here (soon!) forms.gle/d2fCXsrWHVP8...
Ad for the Bioimage Analysis Beginnings Bootcamp at the Broad Institute. 

Where & When
Broad Institute, 415 Main Street, Cambridge MA (in-person only)
Monday–Friday, August 4–8, 20259:00 AM – 5:00 PM

About the Bootcamp
Learn core bioimage analysis skills using open-source tools for light
microscopy in this hands-on, in-person course. The Bootcamp
covers annotation, segmentation, and deep learning fundamentals.

Fee: $600 (Academic/Non-Profit) | $1000 (Industry/For-Profit)
For more information email ImagingAdmin@broadinstitute.org
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Eva de la Serna @sciencedoodles.bsky.social · 22/04/2025
New to bioimage analysis & Python? Want to quantify fluorescence microscopy images, explore segmentation & classification, & try colocalization analysis using Python? If so, this course is for you! Apply by June 1st! 🔬💻https://iac.hms.harvard.edu/bobiac/2025
iac.hms.harvard.edu
BoBiAC | 2025
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Maria Theiss @murriwurri.bsky.social · 22/04/2025
Can highly recommend! Not only is Python one of the most versatile tools in bioimage analysis, but bioimage analysis itself is also an excellent way for visual learners to learn and improve their Python skills! And it is led by fantastic people!
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HMS Image Analysis Collaboratory @hms-iac.bsky.social · 22/04/2025
‼BREAKING‼ We’ve secured new funding for the Boston Bioimage Analysis Course (BoBiAC) this July at Harvard Med School! Course fees down 37%, with fee waivers for academic applicants, for an intensive hands-on intro to bioimage analysis with Python! Apply by June 1st! iac.hms.harvard.edu/bobiac/2025
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FocalPlane @focalplane.bsky.social · 17/04/2025
Are you looking to boost your bioimage analysis skills? If so, check out the Boston Bioimage Analysis Course run by @hms-iac.bsky.social and @citehms.bsky.social! Apply by 16 May 2025 focalplane.biologists.com/2025/04/10/b...
BoBiAC logo incorporating a laptop
Boston Bioimage Analysis Course | 2025
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Simon F. Nørrelykke @simonfn.bsky.social · 15/04/2025
Please join in-person if you are nearby, or by Zoom if not.
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HMS Image Analysis Collaboratory @hms-iac.bsky.social · 14/04/2025
✨We are proudly hosting 𝐏𝐫𝐨𝐟. 𝐒𝐢𝐱𝐢𝐚𝐧 𝐘𝐨𝐮 (MIT)✨ “𝐂𝐨𝐦𝐩𝐮𝐭𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐚𝐱𝐢𝐚𝐥 𝐝𝐞𝐛𝐥𝐮𝐫𝐫𝐢𝐧𝐠 𝐟𝐨𝐫 𝐢𝐬𝐨𝐭𝐫𝐨𝐩𝐢𝐜 𝟑𝐃 𝐦𝐢𝐜𝐫𝐨𝐬𝐜𝐨𝐩𝐲” 𝐀𝐩𝐫𝐢𝐥 𝟐𝟒𝐭𝐡 @ 𝟏𝟏 𝐚𝐦 𝐄𝐃𝐓 (𝐁𝐨𝐬𝐭𝐨𝐧 𝐭𝐢𝐦𝐞, 𝐔𝐒𝐀) Join us on Zoom! harvard.zoom.us/j/9307790905...
Abstract: 
Three-dimensional subcellular imaging is often hampered by diffraction limits in thick, heterogeneous tissues and invalid assumptions about data distribution and imaging systems.

We introduce SSAI-3D, a weakly physics-informed, domain-shift-resistant framework that robustly achieves isotropic 3D imaging.

Demonstrations in various label-free samples, plus validation on publicly available 3D datasets with unknown blurring and noise, confirm its potential for more accurate subcellular analysis.
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Esteban Miglietta @emiglietta.bsky.social · 11/04/2025
Great opportunity if you're in the Boston area and want to learn about bioimage analysis in Python! forum.image.sc/t/boston-bio...
forum.image.sc
Boston Bioimage Analysis Course (BoBiAC)
The Image Analysis Collaboratory and the Core for Imaging Technology & Education at Harvard Medical School are organizing the 💻 Boston Bioimage Analysis Course (BoBiAC). Join us in July for a 6-day in...
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QI@CSHL @qiatcshl.bsky.social · 03/04/2025
Congratulations to students @nancypaniagua.bsky.social & Michal for placing 1st & 2nd place in our @ilastik-team.bsky.social pixel classifier challenge to segment with the least amount of annotations! #lazyannotationsftw
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Matt Lycas @lycasworks.bsky.social · 01/04/2025
Expansion microscopy of a tardigrade
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QI@CSHL @qiatcshl.bsky.social · 31/03/2025
It's TIRF time again at QI!!! 🎉 🔬Check out @jencwaters.bsky.social's infamous TIRF demo to understand the principle behind total internal reflection vs refraction! #gonetirfing #criticallyawesome
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QI@CSHL @qiatcshl.bsky.social · 27/03/2025
QI 2025 student Federico, a computer scientist, oiling an immersion lens for the first time. 💪
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Matt Lycas @lycasworks.bsky.social · 26/03/2025
Demonstrating how local environment impacts fluorescence 🔬🧪🥼@qiatcshl.bsky.social
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Florian Jug @florianjug.bsky.social · 28/03/2025
Love this place… 🥰 @qiatcshl.bsky.social @cshlaboratory.bsky.social
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QI@CSHL @qiatcshl.bsky.social · 29/03/2025
I spy with my little eye...a sneak peek of our light sheet microscopy lab samples! Perks of being a @cshlnews.bsky.social course is access to lots of great sample collecting spots! #catchoftheday #tardigrades
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Florian Jug @florianjug.bsky.social · 28/03/2025
Now that looks like a great new course to check out! More python 🐍 heavy than other courses I know… which is great to have! 👍 Check it out, sign up, learn!!! 🤩
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