internship.

Intern with Zapata Research at the
forefront of quantum.

We can’t believe that 2022 will launch the fifth installment of the Zapata Summer Research Internship Program. With four rounds behind us, there is plenty to reflect on and much to look forward to. See below to learn more.

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Intern Highlight

Intern highlight,
Amara Katabarwa

When Amara first joined Zapata in the summer of 2018 as a research intern, he was studying the characterization of noise in quantum devices as a PhD student at University of Georgia with his supervisor Michael Geller. He brought his expertise to Zapata, where as part of his internship, Amara worked on simulating errors in quantum devices using variational quantum channels as well as developing methods to improve correction of readout errors. After completing his PhD, Amara joined Zapata full-time as a Quantum Research Scientist, leading and/or contributing to numerous projects, including Geometry of Two-Qubit PQCs , experimental demonstrations of Variational Quantum Factoring, quantum generative modeling, and Robust Amplitude Estimation, as well as supervising intern projects. He has recently been promoted to Senior Scientist at Zapata and works as the Lead of Zapata’s Quantum Hardware Team.

Meet Amara

Zapata is a very intellectually diverse and rich environment. It can almost be guaranteed that you can find someone who is interested in almost any particular subfield of near-term quantum computing; from quantum intermediate representations to state preparation algorithms and everything in between.

–

Amara Katabarwa

Meet Amara
Our mindset

We are creative, curious, and revolutionary.

We are committed to creating an environment that accelerates our teammates’ growth and positive impact in the world. We are fast-paced, highly collaborative, and cross-disciplinary. Our world-class team of resourceful problem solvers is pioneering commercial quantum algorithms, research, and product development

Intern program FAQ

FAQ’s

About Zapata

What has Zapata learned throughout the program?

What have Zapata interns done?

Where have Zapata interns landed?

What is next for the intern program?

What has Zapata learned throughout the program?

The Zapata internship program is a well-oiled machine. An essential part of any well-oiled machine is its constant upkeep and improvement. We’ve gotten great feedback from each batch of interns and adjusted the program accordingly. Over time, we’ve learned that project planning led by interns helps create ownership and is a recipe for success (and good papers!). We’ve learned that flexibility to shift focus and follow a promising lead makes for great discoveries. And we’ve learned to keep it simple, because this lets us stay focused on “impact over impress.” 

What have Zapata interns done?

Zapata interns have developed quantum algorithms that take us closer to quantum advantage, they have built software packages that are continuing to be used at Zapata, and they’ve shaped the culture in a wonderful way. 

Where have Zapata interns landed?

Interns from our early cohorts are now postdocs in renowned research groups, lecturers at prestigious universities, and even leaders within Zapata! See below for a list of past Zapata interns and where they are now. 

What is next for the intern program?

In a sense, we don’t exactly know! Intern projects are co-designed and planned between interns and supervisors. So, much is to be determined by you, future Zapata intern. But we will focus on two broad questions: How should we use early fault-tolerant quantum computers to achieve quantum advantage in simulation and optimization and how should we use NISQ devices to achieve quantum advantage in machine learning? While there is much work to be done in answering these questions, the beautiful thing is that our approach to solving these problems, the “Zapata way”, has largely been shaped by an amazing cast of Zapata interns. Thank you! 

Our History

Previous Zapata Research internship classes

meet our team

2021

2020

2019

2018

2021

2021

Ahmed Darwish 

  • Masters Student, Technical University of Munich 
  • Contributions: Quantum Software Team member with contributions throughout our code base 

Mohammad Ghazi Vakili, PhD 

  • Zapata Quantum Industry Postdoc, University of Toronto 
  • Project title: Improving Quantum Enhanced Optimization 

Vladimir Vargas-Calderón 

  • PhD Student, National University of Colombia 
  • Project title: Stay tuned! 

Asad Raza 

Sumner Alperin 

  • PhD Student, University of Toronto 
  • Project title: Orquestra® top 20 – benchmarking optimizers for QCBM 

Phillip Jensen 

  • PhD Student, University of Toronto 
  • Project title: Stay tuned! 

Archismita Dalal 

  • PhD Student, University of Calgary 
  • Project title: Stay tuned!  

Ruizhe Zhang 

Abhinav Anand 

  • PhD Student, University of Toronto 
  • Project title: Stay tuned! 

Sabee Grewal 

  • PhD Student, University of Texas Austin 
  • Project title: Stay tuned! 

Pavan Jayasinha 

  • Undergraduate Student, University of Waterloo 
  • Project title: Efficient training methods for quantum generative models 

Laura Gao 

  • High School Student 
  • Contributions: Quantum Software Team member, expanding QAOA capabilities in Orquestra, initial work on QAOA benchmarking 

2020

2020

Daniel Marti-Dafcik 

  • PhD Student, Oxford University 
  • Project title: Exploration of optimizers for variational quantum algorithms 

Yiqing Zhou 

  • PhD Student, Cornell University 
  • Project title: Improved Bayesian inference module 

Sabee Grewal 

Manuel Rudolph 

Frederic Sauvage 

Kaitlin Gili 

  • PhD Student, Oxford University 
  • Project: Coming soon!  

Daniel Flam-Shepherd 

  • PhD Student, University of Toronto 
  • Project: Reinforcement learning for designing parameterized quantum circuits 

Andrew Pratheepan 

  • Undergraduate Student, University of Ottawa 
  • Contributions: Improvements to Orquestra® 

Ethan Hansen 

  • Undergraduate Student, Case Western Reserve University 
  • Contributions: Orquestra® site and docs, Zapata’s quantum pod, blogs and content creation 

 

2019

2019

Yihui Quek, PhD 

  • Postdoc, University of Berlin 
  • Project title: Grouping techniques for improving measurement overhead for near-term quantum algorithms 

Eric Anschuetz 

  • PhD Student, MIT 
  • Project title: Implementing quantum associative adversarial network (with Cris Zanoci) 

Amir Karamlou 

Cristian Zanoci  

  • PhD Student, MIT 
  • Project title: Quantum circuits for MPS compression (Cris) 

Sukin Sim, PhD 

Tanisha Bassan 

  • Undergraduate Student, University of Toronto 
  • Project title: Numerical investigation of QCBM ansatze and connectivities 

2018

2018

Eric Anschuetz 

Amara Katabarwa, PhD 

Maria Kieferova, PhD 

  • Lecturer at University of Technology Sydney 
  • Project title: Qubit Packing 

Jhonathan Romero, PhD 

Sukin Sim, PhD