Research Associate in AI

King's College London; Greater London; On-site; GBP 45,000 - 47,000; Full time

Job summary

King’s College London is seeking a Research Associate in AI within the Department of Infectious Diseases. The role will develop and apply AI, ML and data-mining methods to address complex research questions in collaboration with clinical partners.

The post is a full-time, fixed-term appointment until 31 August 2028, with pro‑rata professional development leave and opportunities to publish in high-impact journals.

Qualifications

• PhD (or close to completion) in Computer Science, AI, Statistics, or a closely related field.
• Experience with machine learning and deep learning.
• Experience with Generative AI (text and numbers).
• Experience in Agentic AI, orchestration and adaptive systems.
• Experience with mining, classifying and forecasting from heterogeneous data sources.
• Experience in spatial-temporal statistics/modelling.
• Experience with sequence/time-series modelling and language models (transformers).
• Experience with explainable AI methods.

Responsibilities

• Develop and apply AI methods across the project areas and ensure robust, reproducible workflows.
• Lead analysis of large-scale, heterogeneous datasets including sequencing, sensor, and medical data.
• Develop, implement and validate AI methods for ABR and microbiome related research.
• Publish scientific results and contribute to cross-faculty initiatives.

Skills

Machine learning

Deep learning

Generative AI

Agentic AI

Data mining

Spatial-temporal statistics

Time-series modelling

Explainable AI

Education

PhD in Computer Science / AI / Statistics or closely related field

Job description

Research Associate in AI Department: Department of Infectious Diseases

About the role

King’s College London is a world leading research-intensive university with a strong international profile and a long-standing commitment to addressing major societal and global challenges.

This role is based within the Faculty of Life Sciences & Medicine, in the School of Immunology & Microbial Science in the Department of Infectious Diseases.

It brings together expertise across microbiology, immunology, clinical sciences, data science and artificial intelligence.

The Department offers a highly interdisciplinary and collaborative environment, with strong links to clinical partners and access to outstanding research infrastructure and cross faculty initiatives.

About us

This is an exciting project Supported by the BBSRC.

Antibiotic resistance (ABR) is one of the biggest public health challenges of our time.

In 2019, 1.27 million deaths were attributed to antibiotic resistant bacteria.

The gut microbiome is composed of harmless symbionts, commensal bacteria, and opportunistic pathogens, all of which play crucial roles in human and animal health and disease.

In physiological conditions the gut microbiome is stable, but when perturbative events occur (e.g., dietary changes, infections, stress, antibiotic administration) the population of microbiota changes, influencing health and protection against further colonisation.

These changes may involve new resistant bacteria becoming permanent residents or transferring resistance to the commensals).

The core concepts underlying our project are: to gaining a better understanding of how the gut microbiome changes as consequence of infection, co-infection, or treatment (including the development of resistant traits) is a fundamental starting point towards understanding the mechanisms of inception and spread of endemic diseases and antimicrobial resistance.

The research associate will be responsible for developing, implementing and applying artificial intelligence, machine learning, deep learning and data-mining methods to address complex research questions.

They will lead the analysis of large-scale, heterogeneous datasets, including sequencing, sensor, biological and medical data, and ensure robust, reproducible computational workflows.

The postholder will be responsible for developing and applying AI methods across the following areas, demonstrated through scientific publications or other academic/industrial achievements:

• Generative AI (text and numerical data; excluding image, audio, video generation)
• Agentic AI, orchestration, and adaptive systems (continuous feedback, dynamic reasoning, self-optimisation)
• AI methods for mining, classifying, and forecasting from heterogeneous data sources
• Spatial-temporal statistics/modelling from heterogeneous data (Bayesian hierarchical models, autoregressive models, random fields)
• Sequence/time-series modelling and language models, particularly transformer architectures
• Explainable AI methods
• Causal AI methods
• Machine learning

This is a full-time post 35 Hours a week, and you will be offered a fixed term contract until 31st August 2028. Research staff at King’s are entitled to at least 10 days per year (pro-rata) for professional development.

This entitlement, from the Concordat to Support the Career Development of Researchers, applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7.

Visit the Centre for Research Staff Development for more information.

About you

To be successful in this role, we are looking for candidates to have the following skills and experience:

Essential criteria

• PhD (or close to completion) in Computer Science, AI, Statistics, or a closely related field
• Machine learning and deep learning
• Generative AI (text and numbers; excluding image, audio, video generation)
• Agentic AI, orchestration, and adaptive systems (continuous feedback, dynamic reasoning, self-optimisation)
• AI methods for mining, classifying, and forecasting from heterogeneous data sources
• Spatial-temporal statistics/modelling from heterogeneous data (Bayesian hierarchical models, autoregressive models, random fields)
• Sequence/time-series modelling and language models, particularly transformer architectures
• Explainable AI methods

Desirable criteria

• Experience with data analysis in the context of infectious diseases, epidemiology, antimicrobial resistance
• Experience in the development of diagnostics and /or therapeutics solutions, drug-discovery

Downloading a copy of our Job DescriptionFull details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the page.

Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered.

In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant.

Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.

Further Information

At King’s, we believe that the diversity of our community and a culture that is welcoming, open, inclusive and collaborative, are great strengths of the university.The Equality Act of 2010 protects the rights of our students and staff and provides a framework to fulfil our duties to eliminate unlawful discrimination, harassment and victimisation and in addition, to advance equality of opportunity and foster good relations between those who share a protected characteristic and those who do not.

At times, this will include balancing rights and beliefs that can feel in tension.We are committed to free speech and to academic freedom, believing that our foundational purpose as a university, is to create spaces where a wide range of ideas, including ideas that are controversial, can be discussed and debated, and where members of our community can express lawful views without fear of intimidation, harassment or discrimination.When engaging in the robust exchange of ideas, we ask that our community is mindful of our Dignity at King’s guidance.We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the person specification section of the job description.

If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.

Artificial intelligence (AI) is evolving rapidly, and we recognise its growing role in professional work.

Applicants may use AI tools to support preparation of their application, for example to research the role or structure written responses.

However, applications must reflect the applicant’s own work and experience.

AI tools should not be used during interviews or assessment activities unless this has been agreed in advance as a reasonable adjustment.

Further guidance on the use of AI in recruitment can be found here.

We reserve the right to close adverts early due to the volume of applications we receive.

While the closing date may change, all adverts will close at 23:59 to allow sufficient time for applications to be submitted on that day.

Grade and Salary

Grade and Salary : £45,031- 47,379 Including London Weighting Allowance

Job ID : 160725Post Date : 09-Oct-2026Close Date : 10-Nov-2026Contact Person : Professor Tania DottoriniContact Details :