Research Position at the Center for Information Systems and Data Science, Sharif University in Collaboration with a Top-Three Global Institution or medical university school in Bioinformatics.
Projects Descriptions:
1. Utilizing Large Language Models and Retrieval-Augmented Generation (RAG): Applying knowledge graph in medicine, inspired by Stanford University's work.
2. Predicting Profiles for Protein Sequences Using Natural Language Processing: Leveraging the performance of transformers in natural languages by treating protein sequences as a language, similar to Microsoft's research.
3. Applying Manifold Learning and Riemannian Geometry in Protein Dynamics Analysis: Designing and predicting the effects of protein dynamics using approaches akin to those from Cambridge University.
✅Requirements: A bachelor's and master's student with strong implementation skills and clean coding in artificial intelligence, capable of reading and analyzing new Bioinformatics papers, ideating and extensively testing with well-known deep and reinforcement learning architectures, and possessing intermediate Bioinformatics or biology knowledge.
💥This project will be conducted in collaboration with three professors from Sharif University's Computer and Electrical Engineering faculties and supervised by a senior scientist from one of the top three universities in the United States.
🆔To apply and submit your CV, please contact via email with the subject line "Research Position in Bioinformatics": [email protected]
Research Position at the Center for Information Systems and Data Science, Sharif University in Collaboration with a Top-Three Global Institution or medical university school in Bioinformatics.
Projects Descriptions:
1. Utilizing Large Language Models and Retrieval-Augmented Generation (RAG): Applying knowledge graph in medicine, inspired by Stanford University's work.
2. Predicting Profiles for Protein Sequences Using Natural Language Processing: Leveraging the performance of transformers in natural languages by treating protein sequences as a language, similar to Microsoft's research.
3. Applying Manifold Learning and Riemannian Geometry in Protein Dynamics Analysis: Designing and predicting the effects of protein dynamics using approaches akin to those from Cambridge University.
✅Requirements: A bachelor's and master's student with strong implementation skills and clean coding in artificial intelligence, capable of reading and analyzing new Bioinformatics papers, ideating and extensively testing with well-known deep and reinforcement learning architectures, and possessing intermediate Bioinformatics or biology knowledge.
💥This project will be conducted in collaboration with three professors from Sharif University's Computer and Electrical Engineering faculties and supervised by a senior scientist from one of the top three universities in the United States.
🆔To apply and submit your CV, please contact via email with the subject line "Research Position in Bioinformatics": [email protected]
You can’t. What you can do, though, is use WhatsApp’s and Telegram’s web platforms to transfer stickers. It’s easy, but might take a while.Open WhatsApp in your browser, find a sticker you like in a chat, and right-click on it to save it as an image. The file won’t be a picture, though—it’s a webpage and will have a .webp extension. Don’t be scared, this is the way. Repeat this step to save as many stickers as you want.Then, open Telegram in your browser and go into your Saved messages chat. Just as you’d share a file with a friend, click the Share file button on the bottom left of the chat window (it looks like a dog-eared paper), and select the .webp files you downloaded. Click Open and you’ll see your stickers in your Saved messages chat. This is now your sticker depository. To use them, forward them as you would a message from one chat to the other: by clicking or long-pressing on the sticker, and then choosing Forward.
Telegram and Signal Havens for Right-Wing Extremists
Since the violent storming of Capitol Hill and subsequent ban of former U.S. President Donald Trump from Facebook and Twitter, the removal of Parler from Amazon’s servers, and the de-platforming of incendiary right-wing content, messaging services Telegram and Signal have seen a deluge of new users. In January alone, Telegram reported 90 million new accounts. Its founder, Pavel Durov, described this as “the largest digital migration in human history.” Signal reportedly doubled its user base to 40 million people and became the most downloaded app in 70 countries. The two services rely on encryption to protect the privacy of user communication, which has made them popular with protesters seeking to conceal their identities against repressive governments in places like Belarus, Hong Kong, and Iran. But the same encryption technology has also made them a favored communication tool for criminals and terrorist groups, including al Qaeda and the Islamic State.
