Assistant / Associate Professor In Data-Intensive Physics And Ai

Imperial College London; Greater London; On-site; GBP 75,000 - 115,000; Full time

Benefits offered by this job

State-of-the-art facilities

Access to HPC resources

Tailored academic staff training

Job summary

Imperial College London invites applications for an Assistant Professor or Associate Professor in Data-Intensive Physics and AI. The role blends physics research with machine learning, statistics or scientific computing to analyze complex physics datasets and develop robust AI methods.

Applicants should have a PhD in Physics or related field, an independent international research program, and a record of collaboration and funding success. Teaching, supervision, and leadership are expected.

Qualifications

• PhD in Physics or closely related field or equivalent.
• Independent, internationally recognized research programme addressing defined physics questions.
• Experience with large/complex datasets, simulations or data streams in physics.
• Development of novel AI or ML methods for physics analysis and inference.
• Ability to collaborate across the Department and secure external funding.
• Commitment to high-quality teaching and supervision of students.

Responsibilities

• Conduct and publish internationally leading research in data-intensive physics and AI.
• Contribute to undergraduate and postgraduate teaching and curriculum development.
• Supervise PhD students and junior researchers, and mentor colleagues.
• Secure external research funding and foster collaborations within Imperial.
• Participate in departmental and faculty leadership and strategic development.
• Contribute to the MRes in ML and Big Data in the Physical Sciences.

Skills

Research leadership

Teaching & supervision

Collaboration

Communication

Project leadership

Education

PhD in Physics or closely related field

Tools

GPU computing

AI/ML for physics

Job description

The at Imperial College London seeks an outstanding academic to join us as an Assistant Professor or Associate Professor in Data-Intensive Physics and AI. Exceptional candidates may be considered for appointment at Associate Professor level.

Many areas of physics rely on experiments, observatories, missions, and simulations that produce data at increasing scale and complexity. Inferring reliable physical conclusions from these data often requires methods designed around the scientific questions rather than the application of generic tools. We are therefore seeking a Data Physicist who combines a strong research programme in physics with expertise in machine learning, AI, statistics, or scientific computing.

Your research will develop new approaches to analysis, inference and data mining for challenging physics datasets. It will also advance the machine learning and AI methods needed for this work, including the treatment of uncertainty, physical structure, robustness and computational scale. The search is department-wide and welcomes applicants rooted in any area of physics. The appointment will be made on the basis of scientific excellence and the strength of the proposed research programme.

Illustrative areas in which you might work include inference and discovery in large, heterogeneous or high-dimensional physics datasets, simulation-based inference, inverse problems and surrogate modelling, fast and resource-efficient machine learning for real-time analysis, adaptive experimental control and autonomous instruments, and physics-informed and generative AI, including uncertainty quantification, robustness and interpretability. These areas indicate the breadth of the role and do not prescribe particular tools or physics subfields.

As a member of our academic faculty, you will:

• Conduct and publish innovative, internationally leading research within your field .
• Contribute to teaching and curriculum development at undergraduate and postgraduate levels.
• Supervise and mentor PhD students and junior researchers.
• Secure external research funding and build productive collaborations within and beyond Imperial.
• Play an active role in the life and strategic development of the Department and the wider Faculty.
• Serve as a mentor and role model for colleagues and students.
• Contribute to the MRes in Machine Learning and Big Data in the Physical Sciences.
• Help develop proposals for CDT, Doctoral Focal Awards and related doctoral training initiatives, and contribute to their delivery where funded.

Depending on your level of appointment, you may also:

• Contribute to departmental leadership and management.

We are seeking an outstanding academic who is committed to excellence in research, teaching, and contribution to the academic community.

You will be able to demonstrate:

• A PhD in Physics or in a closely related field, or equivalent.
• An independent research programme of international quality that addresses clearly defined questions in physics, evidenced by high-quality publications in peer-reviewed journals (commensurate with your career stage).
• Demonstrated experience in research using large or complex datasets, simulations or data streams in physics, or a track record of developing original AI or machine learning methods for physics analysis and inference.
• Original methodological contributions to data-intensive science, machine learning or AI, evidenced by published research and not limited to the application of existing tools.
• Evidence that your ideas and methods transfer between datasets, simulations, experiments or physics settings.
• The potential to collaborate with researchers across the Department.
• Commitment to high-quality teaching and supervision of students.
• Excellent communication, collaboration, and leadership skills appropriate to your career stage.
• At the Assistant Professor level, you will have clear potential to develop an international reputation in data-intensive physics.
• At the Associate Professor level, you will have an established profile and emerging international recognition, independent scientific leadership including leading a team of researchers, and sustained success in securing external research funding.

It would also be desirable for you to have:

• Experience of developing or deploying methods on accelerated or heterogeneous computing platforms, including GPUs, FPGAs or other specialised hardware, for real-time or large-scale physics applications.

We welcome candidates whose work is grounded in one area of physics. We are looking for methodological depth and ideas that can be applied more widely, not evidence that you already work across several communities.

• The opportunity to continue your career at a world-leading institution and be part of our mission to use science for humanity.
• Access to state-of-the-art facilities, including significant high-performance computing resources through Imperial’s Research Computing Service.
• Grow in your career with tailored training programmes for academic staff including dedicated support with navigating your career and managing research as well as a transparent promotion process.
• Sector-leading salary and remuneration package (including 43 days off a year including public holidays and generous pension schemes).
• Be part of a diverse, inclusive and collaborative work culture with various and resources designed to support your personal and professional .