£•••kAI ResearchgraduateBrompton, ENG, GBhybridfulltimeEducation And SchoolsQiskitPythonPyTorchTensorFlowquantum algorithmsquantum circuitsmachine learningNISQ algorithmsposted
Unlock apply linkApply links and the original listing are a Pro feature — £4.99/mo or £25 once.
Job number
MED05852
Faculties
Faculty of Medicine
Departments
Department of Infectious Disease
Salary or Salary range
£49,017 - £50,893 per annum
Location/campus
Royal Brompton Campus - Hybrid
Contract type work pattern
Full time - Fixed term
Posting End Date
20 Jul 2026
About the role
------------------
Do you have a keen interest in Quantum computing and want to develop new skills and groundbreaking technology for cancer detection as a Research Associate?
Cancer remains one of the most complex diagnostic challenges in modern medicine. Accurate diagnosis is the single most powerful lever we have to improve patient outcomes — and the frontier of quantum computing offers extraordinary new possibilities to transform how we analyse, classify, and detect cancer.
We are seeking an exceptional Research Scientist to join a pioneering project at the intersection of quantum computing and oncological diagnostics. Working within a multidisciplinary team of clinicians, data scientists, and physicists, you will help design and implement quantum-enhanced algorithms to improve cancer diagnosis. This is a rare opportunity to conduct genuinely novel research with direct clinical relevance, using some of the most advanced computational tools available today.
What you would be doing
---------------------------
Key Responsibilities:
* Design and develop quantum computing algorithms for cancer diagnostic applications, including WSI tumour classification, genomic data analysis, and medical image processing.
* Implement and test quantum circuits using Qiskit and related frameworks on both simulators and real quantum hardware (IBM Quantum or equivalent).
* Collaborate with oncologists and clinical data teams to understand diagnostic workflows and translate clinical problems into quantum-amenable computational models.
* Benchmark quantum approaches against classical machine learning baselines, documenting performance, error rates, and scalability.
* Contribute to peer-reviewed publications and internal technical reports summarising research findings and methodologies.
* Present progress to both technical and non-technical stakeholders, including clinical partners and funders.
* Stay abreast of developments in quantum error correction, near-term NISQ algorithms, and emerging quantum machine learning techniques.
* Ensure all research is conducted in accordance with data governance regulations, including applicable NHS data standards and GDPR requirements.
What we are looking for
---------------------------
Essential Requirements:
* PhD in quantum computing, physics, computer science, bioinformatics, or a closely related discipline.
* Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant within the salary range £43,863 - £47,223 per annum
* Demonstrated experience in quantum algorithm development and quantum circuit design.
* Proficiency with Qiskit (IBM's open-source quantum computing framework) — including circuit construction and execution on real or simulated quantum backends.
* Strong programming skills in Python and Pytorch or Tensorflow with experience in scientific computing libraries (NumPy, SciPy, Pandas).
* Solid understanding of machine learning principles and their application to classification or pattern recognition problems.
* Ability to work independently, manage a research timeline, and deliver results within a fixed-term project structure.
* Excellent written and verbal communication skills, with the ability to convey complex technical concepts clearly.
Desirable Requirements:
* Experience applying quantum or classical computing methods to biomedical or clinical datasets (e.g. genomics, histopathology, radiology).
* Familiarity with other quantum frameworks such as PennyLane, Cirq, or Braket.
* Knowledge of quantum machine learning (QML) techniques, including variational quantum classifiers and quantum kernel methods.
* Understanding of cancer biology, diagnostic imaging, or clinical genomics workflows.
* Experience working in regulated environments with sensitive health data.
* Track record of publication in relevant peer-reviewed journals or conferences.
What we can offer you
-------------------------
* Be part of an exciting and groundbreaking research project using quantum computing in cancer research.
* The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
* Access to real quantum hardware through established partnerships
* Grow your career: gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression.
* Sector-leading salary and remuneration package (including 41 days off a year and generous pension schemes).
* Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.
Further information
-----------------------
This is a full-time post (35 hours per week). This role is for a fixed-term contract for 8 months.
The Royal Brompton and Harefield Hospitals are ranked as the top 10 leading hospitals in the world for respiratory and cardiovascular medicine. Together with Imperial College and Brunel University London, you will be part of a team with world leading expertise in cancer diagnosis and detection.
If you require any further details about the role, please contact Jan Lukas Robertus– j.robertus@imperial.ac.uk
Available documents
-----------------------
Attached documents are available under links. Clicking a document link will initialize its download.
Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above.
We reserve the right to close the advert prior to the closing date stated, should we receive a high volume of applications. It is therefore advisable that you submit your application as early as possible to avoid disappointment.
If you encounter any technical issues while applying online, please don't hesitate to email us at support.jobs@imperial.ac.uk. We're here to help.
About Imperial
Welcome to Imperial, a global top-ten university where scientific imagination leads to world-changing impact.
Join us and be part of something bigger. From global health to climate change, AI to business leadership, here at Imperial we navigate some of the world’s toughest challenges. Whatever your role, your contribution will have a lasting impact.
As a member of our vibrant community of 22,000 students and 8,000 staff, you’ll collaborate with passionate minds across nine London campuses and a global network.
This is your chance to help shape the future. We hope you’ll join us at Imperial College London.
Our Culture
We work towards equality of opportunity, to eliminating discrimination, and to creating an inclusive working environment for all. We encourage applications from all backgrounds, communities and industries, and are committed to employing a team that has diverse skills, experiences and abilities. You can read more about our commitment on our web pages.
Proud signatory of the Armed Forces Covenant. We welcome applications from the Armed Forces community.
Our values are at the root of everything we do, and everyone in our community is expected to demonstrate respect, collaboration, excellence, integrity, and innovation.
More AI Research roles like this, weekly
Roles like this expire in about a week. Get new AI Research openings across the UK in your inbox — free, unsubscribe any time.