Internship | QT Quantum Annealing

Quantum computing is a potential game-changer for the energy sector. At this early stage of development, it is still hard to assess its true potential and how to unlock it. The central question is how to create maximum value from QC for this sector.



Education type

university (wo)


Internship and graduation project

Hours a week

Fulltime – 40


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What will you be doing?

Quantum computing could be a potential game-changer for many industries heavily relying on solving large scale inverse and global optimization problem. At this early stage of development, it is still hard to assess its true potential and how to unlock it. A prominent example is the problem of seismic imaging, which is used in near surface surveying for construction projects, identification of hydrocarbon reservoirs, sites of CO2 sequestration, or mapping out of deep subsurface aquifers.

Residual statics estimation (RSE) is an important and computationally challenging problem used to correct the subsurface image. Local, often strong, and unpredictable near-surface wave propagation velocity anomalies result in highly misaligned image of the surface rendering any further subsurface work practically impossible. The RSE aims to determines the additional time shifts (so-called “statics”) for each vertical set of pixels (a trace), such that all traces are optimally aligned and form a (a priori unknown) image of geological structures. 

Naturally there can be many (almost equally viable) solutions to the RSE problem. Each solution corresponds to some local minimum of the objective function, but only one is the best, corresponding to the global minimum. Firstly, when a traditional iterative solver is used to handle this task it is very likely that one gets stuck in said local minimum and never finds the “true” solution. Moreover, we are never able to determine is the solution that we do obtain corresponds to a local or a global minimum. Secondly, other (heuristic) approaches can be used for global optimization (e.g. simulated annealing), however not only they can be computationally very expensive, but too we never know if the (close to) optimal solution has been found. 

In this student assignment we would like make a first step in answering this question by solving the residual statics estimation problem for seismic data, using a quantum annealing computing approach. Starting point of the assignment is the work done by Rothman and Bosisio, in which the residual statics estimation problem is solved by simulated annealing.
  1. The first step would be redoing some of the work of Rothman and Bosisio with a simple, but typical, seismic data set (toy problem with “known solution”).
  2. The second step is solving residual statics estimation problem for the same data set by quantum annealing. This requires finding the appropriate mathematical formulation of the problem (see a formulation in Rothman and Bosisio), translating it into an Ising model or a Quadratic Unconstrained Boolean Optimization (QUBO) problem using appropriate degree reduction methods and minor embedding2 and finally running/solving the problem on an actual D-Wave systems quantum computer. 
  • Time allowing, the final step would be to explore whether there is a potential advantage of using quantum annealing computers and determine the minimum requirements of such a system to solve real sized problems. For this step a realistic seismic dataset will be provided.

What do we require of you?

We expect that the assignment will take 6-9 months. The outcome of the assignment needs to be documented in a report and/or paper and it’s likely that the results will have to be presented on a conference or workshop. A collaboration with an R&D team of a major oil company is currently sought.

We invite master students with a background in (computational) mathematics and/or (quantum) physics and some experience in writing complex code to apply.

What can you expect of your work situation?

TNO is an independent research organisation whose expertise and research make an important contribution to the competitiveness of companies and organisations, to the economy and to the quality of society as a whole. Innovation with purpose is what TNO stands for. With 3000 people we develop knowledge not for its own sake but for practical application. To create new products that make life more pleasant and valuable and help companies innovate. To find creative answers to the questions posed by society. We work for a variety of customers: governments, companies, service providers and non-governmental organisations. Working together on new knowledge, better products and clear recommendations for policy and processes. In everything we do, impact is the key. Our product and process innovations and recommendations are only worth something if our customers can use them to boost their competitiveness. 

What can TNO offer you?

You want to work on the precursor of your career; a work placement gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Naturally, we provide suitable work placement compensation.

Has this vacancy sparked your interest?

Then please feel free to apply on this vacancy! For further questions, send an email to

Contact: Garrelt Alberts
Phone number: 08886 60677

Note that applications via email and third party applications are not taken into consideration.


Apply now


PDEng Garrelt Alberts MSc

  • QuTech
  • Quantum Technology
  • Quantum Computing
  • Quantum Internet
  • System Engineering

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