Applied Quantum Science Team- MSC/PHD Student- Research Lab

Introduction

Haifa Research Lab Emerging Technologies Engineering, a part of IBM Research division, is currently seeking a talented and motivated DevOps student to join our dynamic team. As a member of our lab, you'll have the chance to collaborate with experts in various domains while leveraging our cutting-edge technology portfolio. This is an excellent opportunity to gain hands-on experience in implementing and managing DevOps practices in a research environment, contributing to innovative projects and advancing the state-of-the-art in emerging technologies.

Your work ensures smooth operation of our systems and maintains the highest level of safety for our research environments, directly contributing to the overall productivity of our business.

Your Role And Responsibilities

Are you passionate about quantum computing and eager to work on cutting-edge research with real-world impact?

Join us at IBM Research – Israel as a Student Researcher in a newly formed team dedicated to tackling one of the most exciting challenges in quantum science: achieving quantum advantage.

You will be part of a pioneering team with access to IBM’s most advanced quantum hardware, including the world’s largest quantum computer. Our mission is to explore and solve real-world problems where quantum computing can offer a clear advantage over classical methods.

Research Areas May Include

• Quantum simulation of molecular structures and properties
• Identifying and formulating problems that can demonstrate quantum advantage
• Benchmarking quantum solutions against strong classical approaches to rigorously validate any claimed quantum advantage
  
  

• Option 1: Full-time for 3 at least months
• Option 2: Part-time (2–3 days/week) for at least 1 year
  
  

• Working knowledge of Qiskit, including the ability to translate a Hamiltonian into quantum circuits
• The ability to formulate Hamiltonians for chemical systems or quantum problems
• Working knowledge in quantum machine learning and its comparisons with classical methods
  
  

• Experience with quantum algorithms or variational methods
• Familiarity with quantum chemistry or condensed matter physics
• Strong programming skills in Python