Staff Associate I in the Department of Biological Sciences
Columbia University
See the full job description on jobRxiv: https://jobrxiv.org/job/columbia-university-27778-staff-associate-i-in-the-department-of-biological-sciences/
#bioinformatics #biostatistics #computerscience #datasciences #ScienceJobs #hiring #research
https://jobrxiv.org/job/columbia-university-27778-staff-associate-i-in-the-department-of-biological-sciences/?fsp_sid=10801
I've read a couple of breathless articles about Donald #Knuth's use of #LLM systems, and found (unsurprisingly) that he has a paper about it, if you prefer your news without someone else's hot takes:
https://www-cs-faculty.stanford.edu/~knuth/papers/claude-cycles.pdf
(Sidebar: apparently he's working on *another* volume of #TAOCP? Good lord. I still haven't worked through the exercises in Vol. 1.)

Andriy Burkov's third book is a hands-on guide that covers everything from machine learning basics to advanced transformer architectures and large language models. It explains AI fundamentals, text representation, recurrent neural networks, and transformer blocks. This book is ideal for ML practitioners and engineers focused on text-based applications.
๐ถ Saarland University physicist Prof. Dr. Peter P. Orth and computer scientist Prof. Dr. Markus Blรคser collaborate on QIAPO โ funded with โฌ2.3M by the German Federal Ministry of Research, Technology and Space.
๐ Working with industry partners BMW, Infineon and the quantum computing start-up planqc, their aim is to combine quantum and classical computing to solve optimization problems more efficiently.
Read more: https://sic.link/quantum

Endianness describes how a system orders bytes in memory, and it is a core concept in computer science that affects data encoding, processor design, and cross-platform compatibility.
Here is the difference between little-endian vs. big-endian ๐๐
Find high-res pdf ebooks with all my technology related infographics at https://study-notes.org
#computerscience #operatingsystem #technology #networkengineer #networking
I got dragged into a conversation today where a group of people collectively decided that binary, octal, and hexadecimal number systems are useless and stupid.
Most of them use hexadecimal every day. In their graphic design work. #FF5733 is not decimal. It is HEXADECIMAL.
Their argument against binary was that counting in it is inefficient. That 1, 10, 11, 100, 101 is dumb compared to 1, 2, 3, 4, 5.
These fools fail to understand that both systems are one and the same!
Every positional number system works identically. You have N symbols. You count through them. When you exhaust them, you reset and carry. Decimal has 10 symbols (0-9). Binary has 2 (0-1). Octal has 8 (0-7). Hexadecimal has 16 (0-F). Same mechanism. Different base.
Binary is not inefficient. It maps to transistor states. Octal compresses binary into groups of three-- which is why Unix permissions are written as 000 - 777. Hexadecimal compresses binary into groups of four --which is why every memory address and colour code is in hex. These are not alternatives to decimal. They are the same information at different compression levels.
The people arguing loudest had encountered these systems, used them regularly, and left without a single question about how any of it works.
I do not know what is worse -- the ignorance or the confidence it travels at.
#numbersystems #binary #hexadecimal #octal #computerscience #fediverse #linux #rant
NIC Scientist B Recruitment 2026 โ 243 Group A Posts | Aqubes.com
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