Dr. Kaylee Beine

293 posts

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Dr. Kaylee Beine

Dr. Kaylee Beine

@BeineKaylee

Post-doctoral researcher at University College Dublin Climate change researcher Nature enthusiast

Dublin City, Ireland เข้าร่วม Şubat 2020
331 กำลังติดตาม128 ผู้ติดตาม
Dr. Kaylee Beine รีทวีตแล้ว
Michael Smith Labs
Michael Smith Labs@ubcmsl·
We’re hiring! The Jefferies lab is seeking a Research Assistant/Technician with molecular biology and bioinformatics expertise. Learn more about the position and how to apply at: msl.ubc.ca/careers/ @ubcscience @UBCMicroImmuno
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Dr. Kaylee Beine รีทวีตแล้ว
GMHughes
GMHughes@GrahamMHughes·
Excited to share the Hughes Lab’s 1st 2025 paper, and @ColleenLawless_’s first as first-author, exploreing cuttlefish ink as a chemical defence targeting shark olfactory systems. Great collab with John Finarelli and @OceanExplauren! @UCDSBES @UCD_Research bit.ly/40z7Ype
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Dr. Kaylee Beine รีทวีตแล้ว
Zegni Triki
Zegni Triki@TrikiZegni·
Excited to share I will be joining @UniNeuchatel as an assistant professor early 2025. OFFER: 2 #PhDposition in the new lab. #1 is on zoo animals🐺🐒🦧 and saliva hormones, and #2 is on 🐠 cognition and brains 🧠 Deadline 20 Nov 2024 shorturl.at/NYvVd Spread the word 🙏🏽
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Dr. Kaylee Beine รีทวีตแล้ว
Dr. Kat Wollenberg Valero
new preprint 🧵: In the midst of a week of news coverage about the oceans aproaching the tipping point of becoming too acidic to sustain marine life, we still don't know how most of those species will actually respond to this. #oceanacidification france24.com/en/live-news/2…
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Dr. Kaylee Beine รีทวีตแล้ว
GMHughes
GMHughes@GrahamMHughes·
You can check out our project website for more details and our progress at tridubire.github.io
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Dr. Kaylee Beine รีทวีตแล้ว
Happy Researchers
Happy Researchers@hapyresearchers·
Happy Researchers tweet media
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Dr. Kaylee Beine รีทวีตแล้ว
Matt Dancho (Business Science)
The 10 types of clustering that all data scientists need to know. Let's dive in: 1. K-Means Clustering: This is a centroid-based algorithm, where the goal is to minimize the sum of distances between points and their respective cluster centroid. 2. Hierarchical Clustering: This method creates a tree of clusters. It is subdivided into Agglomerative (bottom-up approach) and Divisive (top-down approach). 3. DBSCAN (Density-Based Spatial Clustering of Applications with Noise): This algorithm defines clusters as areas of high density separated by areas of low density. 4. Mean Shift Clustering: It is a centroid-based algorithm, which updates candidates for centroids to be the mean of points within a given region. 5. Gaussian Mixture Models (GMM): This method uses a probabilistic model to represent the presence of subpopulations within an overall population without requiring to assign each data point to a cluster. 6. Spectral Clustering: It uses the eigenvalues of a similarity matrix to reduce dimensionality before applying a clustering algorithm, typically K-means. 7. OPTICS (Ordering Points To Identify the Clustering Structure): Similar to DBSCAN, but creates a reachability plot to determine clustering structure. 8. Affinity Propagation: It sends messages between pairs of samples until a set of exemplars and corresponding clusters gradually emerges. 9. BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies): Designed for large datasets, it incrementally and dynamically clusters incoming multi-dimensional metric data points. 10. CURE (Clustering Using Representatives): It identifies clusters by shrinking each cluster to a certain number of representative points rather than the centroid. There you have it- my top 10 types of clustering every data scientist needs to know. The next problem you'll face is how to apply them to data science to business. I'd like to help. I’ve spent 100 hours consolidating my learnings into a free 5-day course, How to Solve Business Problems with Data Science. It comes with: 300+ lines of R and Python code 5 bonus trainings 2 systematic frameworks 1 complete roadmap to avoid mistakes and start solving business problems with data science, TODAY. 👉 Here it is for free: learn.business-science.io/free-solve-bus…
Matt Dancho (Business Science) tweet media
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Dr. Kaylee Beine รีทวีตแล้ว
Koenraad Van Meerbeek
Koenraad Van Meerbeek@K_VanMeerbeek·
🚨Job alert: Postdoc position in Ecology 🚨Exciting Opportunity! We are hiring a postdoctoral researcher for the MICROMICS project. Join us to explore how #microclimate shapes adaptive evolution and dispersal dynamics of forest plants! shorturl.at/8AuWf
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Dr. Kaylee Beine รีทวีตแล้ว
Sch. Biol. & Env. Sc
Sch. Biol. & Env. Sc@UCDSBES·
#JobFairy Funded PhD position. Title: Drivers and mechanisms of ecological resilience in freshwater ecosystems
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Dr. Kaylee Beine รีทวีตแล้ว
Katharina Ruthsatz
Katharina Ruthsatz@KRuthsatz·
Liam Connell talking about his research on transgenerational plasticity in the marine ragworm to current and future experimental ocean conditions in the A17 session at #sebconference @SEBiology
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Dr. Kaylee Beine รีทวีตแล้ว
Lauric_Feugere
Lauric_Feugere@LFeugere·
Our Transgenerational Plasticity session is starting in the Zenith room, come see lots of exciting talks today at #SEB24
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Dr. Kaylee Beine รีทวีตแล้ว
SEB @sebiology.bsky.social
Highlights of the first day!
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Dr. Kaylee Beine
Dr. Kaylee Beine@BeineKaylee·
@YountLabOSU I use Inkscape, illustrator is better, but Inkscape gives you .svg files that you can go back and edit more later
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Jacob Yount
Jacob Yount@YountLabOSU·
What software is everyone using for generating high res publication figures? We recently made the switch from Powerpoint to Illustrator, but the university is canceling our Adobe subscription and a monthly fee for everyone in the lab isn't gonna work. 🥲😡😩
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