Current Vacancies
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Key details
- Location UK DRI at King's
- £34,713 - £38,127 per annum
About us:
Researchers at the UK DRI at King’s use innovative approaches to explore the biological mechanisms involved in neurodegenerative diseases. Their goal is to defeat dementia by uncovering vital new knowledge that will lead to the design of smarter diagnostics and effective treatments. The team aim to understand the fundamental biological processes involved in dementia at a molecular level – and to use that knowledge to design new ways to diagnose and treat disease more precisely.
Join the forefront of dementia research at the UK Dementia Research Institute (UK DRI) at King’s College London, where our interdisciplinary research community is dedicated to understanding the molecular mechanisms underlying amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). As part of the Department of Basic and Clinical Neuroscience, the UK DRI at King’s undertakes innovative cellular, molecular and translational research to advance our understanding of neurodegeneration and develop new therapeutic approaches.
About the role:
Dr Jacqueline Mitchell and Prof Marc-David Ruepp are seeking an enthusiastic and organised Research Technician to work on a project to identify the molecular determinants of FUS toxicity in amyotrophic lateral sclerosis (ALS) utilising transgenic mouse models.
This position will require excellent organisational skills and attention to detail, as well as a willingness to undertake occasional weekend and Bank Holiday work where required for the maintenance of mouse colonies.
You will be a reliable and motivated technician with a strong interest in supporting research into the molecular mechanisms underlying neurodegenerative disease.
The Mitchell and Ruepp groups work collaboratively to investigate the molecular mechanisms underlying ALS and related neurodegenerative disorders. You will join a multidisciplinary research environment at the Denmark Hill Campus with a key role in:
- Maintaining and managing transgenic mouse colonies, including breeding, weaning and accurate colony record keeping
- Planning breeding strategies to ensure the timely availability of animals required for experimental studies
- Performing mouse genotyping and analysis of results
- Undertaking routine monitoring and care of mouse colonies and performing licensed procedures as appropriate
- Supporting experimental studies using transgenic mouse models, including tissue collection and processing
- Preparing and sectioning tissues for histological analysis
- Performing immunohistochemical and immunofluorescent staining
- Imaging-stained tissues using slide-scanning and confocal microscopy
- Undertaking routine image analysis using appropriate analytical software
- Maintaining accurate experimental and laboratory records
- Ensuring that work is carried out in accordance with relevant health and safety, animal welfare and regulatory requirements
- Being available and willing to work occasional weekends and Bank Holidays where required for essential mouse-colony duties
This post is offered on a part-time or full-time basis (26.25–35 hours per week) on a fixed-term contract until 31 March 2028, with the possibility of extension subject to further funding.
About you:
To be successful in this role, we are looking for candidates to have the following skills and experience:
Essential criteria
- Hands-on experience working with laboratory mice.
- Demonstrable experience in experimental planning and accurate record keeping.
- Practical skills in working in a laboratory environment.
- Excellent organizational and planning skills.
Desirable criteria
- A current or previous UK Home Office Personal License for work with mice.
- Experience in collection, dissection and processing of mouse tissues.
- Experience in mouse handling, routine procedures, and colony management.
- A degree in a relevant or related biomedical science
- Demonstratable experience of independently managing multiple genetically modified mouse colonies, including breeding strategy and colony planning, weaning, and genotyping.
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Key details
- Location: UK DRI at Imperial
- £50,733 - £59,484 per annum
About the role
We are looking for a curious and highly motivated postdoctoral Research Associate to join a collaborative team to take a central role in a project investigating how TSPO - a mitochondrial protein - protects against vascular dysfunction in early-stage Alzheimer's disease. This British Heart Foundation-funded project sits at the intersection of cardiovascular and dementia research. You will be jointly mentored by Professor David Owen and Dr Samuel Barnes (Group Leader, UK Dementia Research Institute), with both supervisors actively committed to your scientific development and career progression. With membership of the UK DRI, you will also benefit from connection to a national network of multi-disciplinary researchers.
Our groups are committed to flexible working, open science, and creating an environment where everyone can thrive. We are happy to discuss the role informally before you apply.
What you would be doing
Based on promising findings in rodent models, we are running a clinical study to test whether a TSPO ligand improves cerebrovascular function in patients with early Alzheimer's disease, and whether this in turn reduces network hyperexcitability. The role will involve collection of data in study participants using MRI and EEG approaches. A background in cellular biology and data analysis is essential, and a background in neuroscience or vascular are desirable.
What we are looking for
You will hold, or be near completion of, a PhD in neuroscience, psychology, biomedical engineering, physics, cellular biology or a related field, and demonstrate:
- Experience acquiring human neurophysiological or neuroimaging data — EEG, MRI, or both.
- Experience working directly with research participants
- Proficiency in coding, for example in MATLAB, and in handling large-scale neural datasets.
- A developing publication record, with at least one first-author manuscript published or in late-stage revision.
- Knowledge of vascular biology
- Ability to work collaboratively within a multi-disciplinary team.
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Key details
- Location: UK DRI at Imperial
- Salary: This PhD position includes a tax-free stipend of £23,805 per annum and Home fees for 3 years, and up to six months of writing up stipend if required.
About the Project
Applications are invited for a 3-year PhD studentship funded by the Edmond J. Safra Foundation within Dr Cynthia Sandor’s group in the Department of Brain Sciences at Imperial College London.
This studentship will focus on:
Predicting Insulin Resistance from Blood Transcriptomes: A Peripheral Window onto Brain Insulin Resistance in Parkinson’s and Alzheimer’s Disease
The successful candidate will be based at Imperial’s White City Campus and will join an active and collaborative postgraduate community. The project will be supervised by Dr Cynthia Sandor, an Edmond and Lily Safra Assistant Professor in Parkinson's Disease in the Department of Brain Sciences, and a UK DRI Group Leader.
Background
Parkinson’s disease affects over 10 million people worldwide and its prevalence is increasing with ageing populations. Type 2 diabetes and insulin resistance are established risk factors for Parkinson’s disease. Increasingly, attention has turned to brain insulin resistance, a state in which neurons themselves respond poorly to insulin, with impaired signalling. Unlike peripheral insulin resistance, brain insulin resistance reflects blunted neuronal insulin action and has been linked to mitochondrial dysfunction, α-synuclein aggregation, and neuroinflammation, yet its genetic and biomarker basis in Parkinson’s disease remains poorly understood.
Recent work from Dr Sandor’s group and collaborators (Volpato et al. 2025) has shown that vulnerable dopamine-producing neurons show increased activity in renin–angiotensin system signalling and metabolic stress pathways, and that genetic risk for Parkinson’s overlaps with risk for type 2 diabetes and cardiometabolic traits. Epidemiological studies also suggest that certain blood pressure and diabetes medications may reduce Parkinson’s risk, but we do not yet know which patient subgroups benefit most. A central obstacle is that brain insulin resistance cannot be measured directly at scale in patients, which motivates an accessible, blood-based readout that can stratify individuals and probe the metabolic dimension of neurodegeneration across large cohorts.
Project Overview
This PhD project will develop and validate a computational model that predicts insulin resistance from peripheral blood mononuclear cell (PBMC) transcriptomes, and apply it to existing Parkinson’s and Alzheimer’s disease PBMC datasets. Peripheral insulin resistance is directly predictable from blood and is only partially coupled to brain insulin resistance, so the PBMC-derived score is positioned as a scalable, blood-based proxy for the central process rather than a direct measure of it. The project is entirely computational and combines machine learning with single-cell and bulk transcriptomics and rigorous cross-dataset validation.
Key objectives include:
- Signature derivation: Train a transferable insulin-resistance predictor on metabolically labelled reference cohorts using regression and classification models with per-cell-type pseudobulk analysis to localise the signature to specific immune subsets.
- Data integration & validation: Harmonise heterogeneous single-cell and bulk PBMC datasets (using Harmony, scVI/scANVI and ComBat), explicitly controlling for age, sex, BMI, medication and ancestry, and validate the signature with strict leave-one-dataset-out cross-validation and an external labelled cohort.
- Transfer to PD cohorts: Apply the validated signature to existing Parkinson’s PBMC datasets to impute per-subject and cell-type-resolved insulin-resistance scores, and test whether these scores are elevated relative to controls and track disease severity and cognition.
- Brain-IR alignment: Where central insulin-resistance anchors are available (for example intranasal-insulin EEG/fMRI, FDG-PET, or published brain insulin-resistance signatures), correlate the peripheral score with these measures to establish how far the blood-based readout reflects the brain process.
Training and Environment
The student will receive training in:
- Machine learning for transcriptomic prediction (regression and classification)
- Single-cell and bulk RNA-seq analysis, batch integration and cell-type deconvolution
- Rigorous cross-dataset validation, confound control and reproducible research
- Integrative analysis of multi-omic and clinical data across neurodegenerative cohorts
This project provides an excellent opportunity to gain experience at the interface of machine learning, single-cell transcriptomics, and translational neuroscience.
Requirements
Applicants should hold a First Class or Upper Second-Class degree (or equivalent) in bioinformatics, computational biology, data science, statistics, machine learning, or a related quantitative discipline. A Master’s degree in a relevant field (data science, computational neuroscience, statistical genetics) is desirable. Strong programming in R or Python and an interest in single-cell transcriptomics, machine learning and large-scale cohort analyses are advantageous.
Application Process
To apply, please send the following to Dr Cynthia Sandor (c.sandor@imperial.ac.uk) or Dr Katarzyna Zoltowska (k.zoltowska@imperial.ac.uk).
- Your CV
- A brief statement outlining your research interests and motivation
- Contact details for two academic referees
For informal enquires, please contact Dr Sandor or Dr Zoltowska.