דרושים Phd Research Intern Computer Vision Deep Learning - ב-אנבידיה ב-ארהב

What you'll be doing:

• Path-find technical innovations in Quantum Error Correction and Fault Tolerance, working with multi-functional teams in Product, Engineering, and Applied Research

• Develop novel approaches to quantum error correction codes and their logical operations, including methods for implementation and logical operation synthesis

• Research and co-design improved methods to achieve fault tolerance, such as techniques for logical operations, concatenation, synthesis, distillation, cultivation, or others

• Collaborate with internal teams and external partners on developing technology components to enable a fault-tolerant software stack integrated with quantum hardware

• Adopt a culture of collaboration, rapid innovation, technical depth, and creative problem solving

What we need to see:

• Degree in Physics, Computer Science, Chemistry, Applied Mathematics, or related engineering field or equivalent experience (Ph.D. preferred)

• Extensive background in Quantum Information Science with 8+ overall years of experience in the Quantum Computing industry

• A demonstrated ability to deliver high impact value in quantum error correction and fault tolerance

Ways to stand out from the crowd:

• Hands-on experience in scientific computing, high-performance computing, applied machine learning, or deep learning

• Experience with co-design of quantum error correction with quantum hardware or quantum applications

• Experience with CUDA and NVIDIA GPUs

• Passion to drive technology innovations into NVIDIA software and hardware products to support Quantum Computing

What you’ll be doing:

• Understand, analyze, profile, and optimize AI training workloads on state-of-the-art hardware and software platforms.

• Guide development of future generations of artificial intelligence accelerators and systems.

• Develop detailed performance models and simulator infrastructure for computing systems accelerating AI training, and implement and evaluate hardware feature proposals.

• Collaborate across the company to guide the direction of machine learning at NVIDIA; spanning teams from hardware to software and research to production.

• Drive HW/SW co-design of NVIDIA’s full deep learning platform stack, from silicon to DL frameworks.

What we need to see:

• PhD in CS, EE or CSEE and 3+ years; or MS (or equivalent experience) and 6+ years of relevant work experience.

• Strong background in computer architecture, with a proven track record of architecting features in shipping high-performance processors.

• Background in artificial intelligence and large language models, in particular training algorithms and workloads.

• Experience analyzing and tuning application performance on state-of-the-art hardware.

• Experience with processor and system-level performance modelling, simulation, and evaluation before silicon exists.

• Programming skills in C++ and Python.

• Familiarity with GPU computing across all layers of the AI stack, from DL frameworks like PyTorch down to CUDA.

What you’ll be doing:

• Develop and test sample applications for chemistry and materials discovery using artificial intelligence.

• Help develop AI first workflows using NVIDIA technology and popular deep learning frameworks.

• Create clear, practical examples and documentation for developers and researchers.

What we need to see:

• Pursuing a PhD in Chemistry, Materials Science, Computer Science, or a related field.

• Familiarity with AI/ML concepts and experience with at least one deep learning framework (e.g., PyTorch, TensorFlow).

• Basic understanding of chemistry or materials science principles.

Ways to stand out from the crowd:

• Experience with GPU programming or CUDA and machine learning frameworks such as PyTorch.

• Contributions to open-source projects related to AI or scientific computing.

• Coursework or projects involving AI for scientific applications.

You will also be eligible for Intern

NVIDIA is searching for a world-class researcher in generative AI to join our research team. You will be conducting original research for generative AI applications, including image generation, video generation, 3D generation, and audio generation. You will be working with a team of world-class researchers eager to make great impacts with generative AI models. You will be building research prototypes and scaling them with large datasets and compute. After building prototypes that demonstrate the promise of your research, you will work with product teams to help them integrate your ideas into products.

What you'll be doing:

• Conduct original research in the space of generative AI

• Implement and train large-scale generative AI models for various content creation applications

• Collaborate with other research team members, a diverse set of internal product teams, and external researchers

• Have a broader impact through the transfer of the technology you've developed to relevant product groups

What we need to see:

• Ph.D. in Computer Science/Engineering, Electrical Engineering, or a related field (or equivalent experience).

• 5+ years of relevant research experience.

• Excellent collaboration and interpersonal skills

• Excellent python/C++ programming skills

• Great knowledge of common deep-learning frameworks

• Experience in processing or curating large-scale datasets

• Excellent knowledge of theory and practice of deep learning, computer vision, natural language processing, or computer graphics

• Track record of research excellence or significant product development

What you'll be doing:

• Path-find technical innovations in Quantum Error Correction and Fault Tolerance, working with multi-functional teams in Product, Engineering, and Applied Research

• Develop novel approaches to decoding quantum error correction codes and their logical operations, including researching advanced implementations in hardware

• Research and co-design improved methods to achieve more scaled decoders

• Collaborate with internal teams and external partners on developing technology components to enable a fault-tolerant software stack integrated with quantum hardware

• Adopt a culture of collaboration, rapid innovation, technical depth, and creative problem solving

What we need to see:

• Masters degree in Physics, Computer Science, Chemistry, Applied Mathematics, or related engineering field or equivalent experience (Ph.D. preferred)

• Extensive background in Quantum Information Science with 6+ overall years of experience in the Quantum Computing industry

• A demonstrated ability to deliver high impact value in quantum error correction and decoding

Ways to stand out from the crowd:

• Hands-on experience in scientific computing, high-performance computing, applied machine learning, or deep learning

• Experience with co-design of quantum error correction with quantum hardware or quantum applications

• Experience with CUDA and NVIDIA GPUs

• Passion to drive technology innovations into NVIDIA software and hardware products to support Quantum Computing

What you'll be doing:

• Develop and refine deep learning models and techniques for genomics analysis, including but not limited to DNA sequencing, variant calling, and model prediction.

• Advance and apply modern Deep Learning techniques to develop Large Language Models (LLMs), Graph Neural Networks, Graph Transformer Networks, and comprehensive multi-modal models in genomics.

• Design and implement machine learning techniques to tailor foundation models for downstream genomic specific tasks.

• Generate and manage datasets for large-scale machine learning, focusing on learning from genomics specific applications.

• Collaborate closely with product and hardware architecture teams to ensure flawless integration of research and development into NVIDIA products.

• Work in tandem with engineering and AI research teams to employ the latest technologies for scalable and innovative genomics analysis.

What we need to see:

• Master or Ph.D. in Computer Science, Bioinformatics, or Computational Biology, or related field (or equivalent experience).

• 3+ years of experience in related field.

• Proficiency in C/C++ and Python, with a strong grasp of software design and programming principles.

• Background with Large Language Models (LLMs) and natural language processing (NLP), Generative AI and Foundation Models.

• Strong proficiency with modern frameworks such as PyTorch and TensorFlow, Experience with Large scale inferencing.

• Experience in building and implementing complex algorithms and data structures, with a focus on bioinformatics or genomics applications.

• Deep understanding of computer system architecture, operating systems, and the challenges associated with large-scale genomic data analysis.

Ways to stand out from the Crowd:

• Hands-on experience in using LLM, Graph Neural Network, Graph Transformer Network particularly those applied to genomics data.

• Strong collaborative and interpersonal skills to effectively work and influence within a dynamic, technical environment.

• Ability to decompose complex requirements into step by step tasks and reuse available solutions to implement most of those.

What you'll be doing:

• Path-find technical innovations in Quantum Error Correction and Fault Tolerance, working with multi-functional teams in Product, Engineering, and Applied Research

• Develop novel approaches to quantum error correction codes and their logical operations, including methods for implementation and logical operation synthesis

• Research and co-design improved methods to achieve fault tolerance, such as techniques for logical operations, concatenation, synthesis, distillation, cultivation, or others

• Collaborate with internal teams and external partners on developing technology components to enable a fault-tolerant software stack integrated with quantum hardware

• Adopt a culture of collaboration, rapid innovation, technical depth, and creative problem solving

What we need to see:

• Masters degree in Physics, Computer Science, Chemistry, Applied Mathematics, or related engineering field or equivalent experience (Ph.D. preferred)

• Extensive background in Quantum Information Science with 12+ overall years of experience in the Quantum Computing industry

• A demonstrated ability to deliver high impact value in quantum error correction and fault tolerance

Ways to stand out from the crowd:

• Hands-on experience in scientific computing, high-performance computing, applied machine learning, or deep learning

• Experience with co-design of quantum error correction with quantum hardware or quantum applications

• Experience with CUDA and NVIDIA GPUs

• Passion to drive technology innovations into NVIDIA software and hardware products to support Quantum Computing