Youchao (Davin) D.’s Post

As promised, here's the link about the second role: OMSCS is hiring again! There are two positions we're hiring for, both Research Technologists. Since LinkedIn only lets me elegantly include one link per post, I posted about one on Monday, and here's a second one for Wednesday. Generally, research technologists are software engineers with a slant toward building technologies to support/conduct research. This second Research Technologist role looks at applications of AI to at-scale and computer science education. It will look at large language models for formative feedback, generative AI-assisted rapid content creation, and AI assistance for more routine tasks at scale. The position is full-time and remote-capable, so candidates can live anywhere in the United States. The role's rank is either Research Technologist II or Senior Research Technologist, meaning a Master's degree is required... although I have a feeling I know where to find a lot of students with Master's degrees in computer science. Maybe. Applications are open through 11/30. If you're interested, read more and apply below! (Or if that doesn't work because the site can sometimes play poorly with links, you can check it out on Inside Higher Ed's job listings as well: https://lnkd.in/gg3Wv8sP)

Deep Learning Theory and Algorithms

This is an exciting opportunity for Ph.D students. #phd #phdposition #PhDOpportunity #GraduateStudents #HigherEducation #AcademicOpportunity #ResearchOpportunity #PhDLife #AcademicProspects #PhDJourney #Scholarship #PhDCommunity #GradSchool #EducationOpportunity #PhDResearch #FutureScholars #CareerDevelopment #statistics #machinelearning #mathematics #math

Great opportunities

Super interesting research questions to explore under one of the best professors I have met and learned from. Would highly recommend applying to her!

Transitioning from #research to #industry can be quite the journey - speaking from my own experience! The skills honed in research, like hypothesis establishment, asking the right questions, and data analysis, are incredibly valuable in industry too (minus the luxury of time, of course 😅). I'm personally committed to supporting young PhDs in pursuing practical #climatesolutions. If you're one of them, I encourage you to apply here! #Sustainability #ClimateAction #PhDCommunity

Whether you're a student seeking your next opportunity or a professional looking to fill a position, our channel is here to serve you! We list positions for all levels - from internships to postdocs - in various specializations like AI, Machine Learning, Robotics, and more. Want to advertise a position? Send it to Soroush Vahidi or Afshin Zeinaddini Meymand. This channel is free, aiming to share the open positions worldwide. Use our hashtags to find opportunities easily: #job, #phd, #internship, #AI, #DataScience, #remote, and many more. The link to the channel: https://t.me/cspositions #ComputerScience #CareerOpportunities

The NSF Mathematical Sciences Graduate Internship (MSGI) Program offers fully-funded practical research opportunities for graduate students at DOE laboratories, including remote or onsite options. This is an opportunity for the students to both enhance their research skills and apply their academic knowledge to challenging real-world problems. Students can apply through January to this program. Learn more here: (https://lnkd.in/geta_Zhg). I have three projects so the interested students can work with our group at the Mathematics and Computer Science Division, Argonne National Laboratory this summer (see https://lnkd.in/gvq-et7F fro more information). 1. Reliability and Robustness in Scientific Large Language and Foundation Models [Project code: ANL-Madireddy2]:  This project focuses on developing robustness and uncertainty quantification methods for large language models and foundation models in scientific domains (see our recent paper on foundation model for weather/climate:https://lnkd.in/gRzZ2Rk6), aiming to enhance their reliability and controllability in areas like climate modeling and cosmology. It involves integrating probabilistic modeling and advanced training techniques, and exploring strategies for adversarial robustness and fine-tuning, contributing to the emerging field of trustworthy and reliable AI in scientific research. 2. Probabilistic and Physics-Preserved Neural Networks [Project code: ANL-Madireddy3]:  This project aims to leverage a differentiable Bayesian network architecture search approach developed recently in our group to build physics-preserved neural networks for coupled PDE-driven problems such as nuclear fusion and fission. By integrating sparse priors and innovative pruning strategies, the framework seeks to discover best performing architectures with quantified uncertainty. The focus will be on incorporating physics information from differential equations directly into the neural architecture through such an approach, enhancing the model's performance and reliability. 3. Robust Continual Learning through the Lens of Robust Optimization [Project code: ANL-Madireddy4]:  This project aims to enhance continual learning in machine learning, crucial for edge computing and language model adaptation. It focuses on developing robust optimization techniques to overcome sensitivity to task sequence order. This includes using "Worst-Case Scenario Analysis" for performance in challenging conditions, "Adversarial Training" for resilience, and "Uncertainty Modeling" for informed decision-making. The student in this project will be co-supervised by Sven Leyffer and Angel Yanguas-Gil If you are a graduate student interested in these projects and has applied and/or planning to apply to the NSF-MSGI program. Feel free to reach to me if you have any additional questions. #trustworthyai #continuallearning #SciML #optimisation #foundationmodels #llm #summerinternship2024

🚀 Exciting Journey into Quantum Computing! 🌌 During my internship at DRDO, I delved into the fascinating world of Quantum Computing. Undoubtedly I can say that it is most fascinating field in Computer Science.🧬💻 Many of you have asked me about it, so here's a brief insight: 🌟 What is Quantum Computing? Quantum computing is a revolutionary field that leverages the principles of quantum mechanics to process information in a fundamentally different way than classical computers. It uses qubits (quantum bits) to perform complex calculations at speeds unimaginable with traditional computers. 📚 How to Get Started? Foundations: Start with a strong grasp of linear algebra and quantum mechanics. Resources like MIT's OpenCourseWare are excellent for this. Programming: Learn quantum programming languages like Qiskit, Cirq, or Quipper. Hands-On: Practice on quantum simulators and real quantum hardware available on platforms like IBM Q Experience and Rigetti Forest. Community: Join quantum communities online, like Quantum Computing Stack Exchange and follow experts on Twitter or LinkedIn. 🌐 Quantum computing is set to revolutionize industries like cryptography, drug discovery, and optimization. It's an exciting field with limitless potential! 💡 Feel free to reach out for more information, and let's explore the quantum frontier together! 🌌🚀 #quantumcomputing #quantum #twitter #internship #computerethics

Check out this blog on an important topic about Women in Quantum below: