Computer Scientist

The postholder will join a team of AI specialists, informaticians, statisticians and clinicians to build digital twins for clinical trials in motor neuron disease (MND, also known as ALS). This post sits within the Department of Basic and Clinical Neuroscience (https://www.kcl.ac.uk/neuroscience/about/departments/basic-clinical-neuroscience), working closely with Biostatistics and Health Informatics (https://www.kcl.ac.uk/bhi), and will be part of a team working to digitally simulate populations of people with motor neuron disease for the purposes of clinical trial design and optimisation. The role sits within the UK Motor Neuron Disease Research Institute (https://ukmndri.org) and the NIHR BRC Motor Neuron Disease theme (https://www.maudsleybrc.nihr.ac.uk/research/motor-neuron-disease-mnd/), and is part of the Precision ALS programme in the TRICALS Consortium, Europe’s largest MND research initiative. We are looking for an independent thinker who wants to be part of a growing team to lead bioinformatics methodology and improve the efficiency of trial designs within the MND space. The aim is to accelerate the search for a cure for MND, working with the clinical and statistics team members modelling digital twins in a virtual population. The results will be suitable for informing clinical trial design and potentially providing evidence of the predicted placebo effect in trials where a placebo arm was absent. The postholder will work with the statistical, computing and clinical teams to develop and test a simulated digital twins model, including developing relevant code and running simulations, handling clinical trial data compliant with data, confidentiality and ethics rules, working within a Trusted Research Environment to access clinical data. The postholder should be capable of performing the modelling using multiple approaches, taking into account issues such as waiting times, disease progression rates, disease heterogeneity, correlated clinical and biological features and their effects on the model. Methods will include development of digital twins using simulation, deep learning, AI, and large language models, with validation against real world populations from a national register, clinical trials and clinic registers, including the ability to model the natural biases of each data source. This is a full time post (35 hours per week), and you will be offered a fixed term contract until 05/11/27 Research staff at King’s are entitled to at least 10 days per year (pro-rata) for professional development. This entitlement, from the , applies to Postdocs, Research Assistants, Research and Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. 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To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria * PhD qualified in relevant subject area

• Post-graduate degree in computing, informatics, bioinformatics or related subject
• Considerable understanding of clinical and biological datasets and data modelling
• Knowledge/experience in simulation, large language models, AI, deep learning, statistical methods
• Experience of working as the technical expert in a multidisciplinary team

Desirable criteria * Experience working with clinical trial or routinely collected healthcare data

• Experience analysing large, complex, or longitudinal datasets
• Experience developing and validating computational models using statistical, simulation and/or AI-based approaches.
• Experience as the bioinformatics lead in published medical research
• To have published in leading clinical journals with a clear position of contribution commensurate with a Research Excellence Framework of at least nationally relevant impact

Grade and Salary : £53,947 - £61,660 per annum, including London Weighting Allowance Job ID : 154365

We are part of the King’s MND Care and Research Centre, a prize-winning internationally recognized group of clinical and laboratory research teams working to accelerate the search for a cure for motor neuron disease (also known as ALS). We work across King’s College London and King’s College Hospital at the Denmark Hill site., 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.