Postdoctoral researcher in Science Operations (UK-Based)

SKA Observatory; Jodrell Bank; On-site; GBP 42,000 - 60,000; Full time

Benefits offered by this job

30 days annual leave and publichols

Pension scheme

Relocation visa support

Job summary

SKA Observatory, based at the Global Headquarters in the UK (Jodrell Bank), seeks a Postdoctoral Researcher to explore ML/AI techniques for efficient observatory operations. The role supports planning for SKA-Low and SKA-Mid during construction and commissioning phases.

The successful candidate will collaborate with scientists, engineers and software developers to turn operational needs into testable ML/AI solutions, with potential for up to 25% of employed hours for personal research.

Qualifications

• PhD in Astronomy, Physics, Computer Science, Data Science or closely related field, or equivalent.
• Expertise in radio astronomy with ML/AI tools, or ML/AI techniques for the physical sciences.
• Ability to communicate technical work clearly to scientists, engineers and non-specialists.
• Ability to work independently and in distributed teams.

Responsibilities

• Identify and prioritise opportunities where ML/AI can improve observatory operations.
• Develop, train, test and validate ML/AI models using real/archival data.
• Evaluate performance, robustness and reproducibility of ML/AI approaches.
• Collaborate with software/engineering teams to integrate ML/AI tools into operational software/workflows.
• Contribute to development and refinement of Operations workflows relating to ML/AI.
• Document methods, results and recommendations for continuity and scalability.
• Communicate results to SKA staff and wider community; present at meetings.
• Optionally pursue a personal research programme up to 25% of hours.
• Undertake any other duties as directed.

Skills

ML/AI in physical sciences

Radio astronomy techniques

Communication skills

Independent and collaborative work

Education

PhD or near submission in Astronomy/Physics/CS/Data Science

Tools

ML/AI tools

Software engineering practices

Job description

This is a one-year fixed term position and is based at the SKAO Headquarters at Jodrell Bank, Cheshire, UK.

At the SKAO we are coordinating a global effort to deliver one of the largest science facilities on the planet. The SKAO telescopes will be next-generation instruments that will help to answer key questions in astrophysics, drive technological innovation and support human capital development.

More than a dozen partner countries and over a thousand scientists and engineers around the world are already on board, making the SKA project an international collaboration like no other, and one of the most ambitious science and engineering endeavours of the 21st century.

Headquartered in the UK, with telescope sites in Australia and South Africa, the SKAO will be one observatory operating two telescopes, an endeavour spanning three continents. Multinational by design, in early 2021 the SKAO became an intergovernmental organisation, one of only a select handful of science infrastructures to do so worldwide.

Our Global HQ is located near the buzzing city of Manchester at the historic Jodrell Bank Observatory, a UNESCO World Heritage site located in the Cheshire countryside. It is home to a rapidly expanding international team of more than a hundred, working in a highly collaborative and inclusive way, in coordination with SKAO teams in Australia and South Africa as part of a global astronomy and engineering community.

Being part of Team SKA means contributing to something extraordinary: a uniquely exciting project to advance human knowledge that will last for decades. In return, we offer a diverse multicultural working environment, 30 days annual leave plus public holidays, a generous pension scheme, visa and support with relocation (if applicable), regular social events, a family-friendly environment and much more. Come and join us!

An exciting 1-year opportunity for an early-career researcher with expertise in machine learning and artificial intelligence to help shape how these techniques are used in the operations of a world-leading radio observatory.

The Role

The SKAO Science Operations group is seeking to employ a talented and motivated Postdoctoral Researcher to join our team based in the SKAO Global Headquarters located at Jodrell Bank in the UK. This is a fixed-term position for 1 year.

With both SKA-Low and SKA-Mid now in the construction and commissioning phases, planning for operations has entered an exciting phase. Modern radio telescopes generate data volumes and operational complexity on a scale that makes machine learning and artificial intelligence increasingly attractive tools. This role will explore, prototype, and evaluate ML/AI techniques to support efficient, reliable observatory operations in areas such as observation scheduling, telescope and data quality monitoring, anomaly and RFI detection, and support for our user community.

The successful candidate will be highly skilled in communication, as well as in collaborative and inclusive work practices. They will work closely with scientists, engineers and software developers to turn operational needs into well-defined, testable ML/AI solutions. To facilitate this we are seeking a researcher with either a PhD in radio astronomy and practical experience with ML/AI tools, or a PhD in computer science or equivalent fields with demonstrated expertise in implementing ML/AI techniques for the physical sciences. PhD candidates nearing submission will also be considered.

The appointee will be encouraged to carry out research up to 25% of employed hours. Appropriate support, including conference travel, will be provided.

SKAO is committed to providing an inclusive and flexible working environment, meeting the requests of our Colleagues whilst also fulfilling the needs and objectives of the Observatory. This role may be offered on a full-time or part-time basis. Please raise your preference in your application.

Due to the locations involved in the SKA project, in particular the UK and Australia, this role requires the post holder to work across different time zones and, in line with SKAO policy, flexible working hours will be supported in agreement with the line manager.

Informal enquiries may be made to Sarrvesh Sridhar ([e-mail]).

Key Responsibilities, Accountabilities and Duties

The successful candidate will support the future science operations of the SKAO in the following ways:

• Identify and prioritise opportunities where ML/AI techniques can improve the efficiency, reliability and quality of SKAO observatory operations;
• Develop, train, test and validate ML/AI models and prototypes using commissioning, simulated and archival radio astronomy data;
• Evaluate the performance, robustness and limitations of ML/AI approaches against operational requirements, including explainability and reproducibility;
• Work with software and engineering teams to understand how ML/AI tools could be integrated into SKAO operational software and workflows;
• Contribute to the development and refinement of the Operations workflows where it relates to the use of ML/AI;
• Document methods, results and recommendations clearly so that the work can be continued and built upon;
• Effectively collaborate with SKA staff across the three sites;
• Communicate openly, effectively and respectfully with internal and external stakeholders, and present results at internal meetings and to the wider community;
• Optionally undertake a programme of personal research up to 25% of employed hours;
• Undertake any other duties as directed.

Mandatory Knowledge, Skills and Experience

The post holder will have:

• A University PhD degree (or close to submission) in Astronomy, Physics, Computer Science, Data Science or another closely related and relevant field, or equivalent qualification.
• Either (a) expertise in radio astronomy techniques together with practical experience of applying ML/AI tools, or (b) demonstrated expertise in implementing ML/AI techniques to solve problems in the physical sciences.
• Demonstrated ability to communicate technical work clearly, in writing and verbally, to audiences that include scientists, engineers and non-specialists.
• Ability to work both independently and collaboratively within a globally distributed team.

Desirable Knowledge, Skills and Experience

• Experience applying ML/AI to time-series, imaging, anomaly detection, classification or optimisation problems.
• Familiarity with radio interferometric data and processing (e.g. visibilities, calibration, RFI flagging), or a willingness to learn quickly.
• Experience with software engineering best practice, including version control, testing and deploying models in production or near-production environments.
• An appreciation and understanding of the science cases motivating the SKA Observatory.

Equality Diversity and Inclusion Statement

SKA Observatory recognises that our diversity is a strength. We aim to create a welcoming and inclusive environment where everyone feels they belong, and diverse perspectives and ideas thrive. As such, Equality, Diversity, and Inclusion are at the core of SKA Observatory’s agenda.

Our aim is to recruit and retain the most talented individuals, regardless of gender, race, disability, age, sexual orientation, marital status, religion, nationality or background.

Women have traditionally been under-represented in the fields of science and engineering; SKA Observatory welcomes and encourages female applicants.

Where applicants with a disability need facilities or adjustments to enable them to participate in the recruitment process, these will be provided.

SKA Observatory welcome all candidates, especially those from member countries.