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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]



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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]

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Telegram Be The Next Best SPAC

I have no inside knowledge of a potential stock listing of the popular anti-Whatsapp messaging app, Telegram. But I know this much, judging by most people I talk to, especially crypto investors, if Telegram ever went public, people would gobble it up. I know I would. I’m waiting for it. So is Sergei Sergienko, who claims he owns $800,000 of Telegram’s pre-initial coin offering (ICO) tokens. “If Telegram does a SPAC IPO, there would be demand for this issue. It would probably outstrip the interest we saw during the ICO. Why? Because as of right now Telegram looks like a liberal application that can accept anyone - right after WhatsApp and others have turn on the censorship,” he says.

The messaging service and social-media platform owes creditors roughly $700 million by the end of April, according to people briefed on the company’s plans and loan documents viewed by The Wall Street Journal. At the same time, Telegram Group Inc. must cover rising equipment and bandwidth expenses because of its rapid growth, despite going years without attempting to generate revenue.

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