List of available PhD projects
For information on applying for postgraduate study in the Department of Psychology for 2027 entry, please see our application procedure page.
For further information about any of the research projects listed below, please contact the relevant supervisor directly.
Prospective applicants are also encouraged to approach potential supervisors with their own research ideas. Please note that the projects listed are not exhaustive, and additional research opportunities may be available with other academic staff in the Department.
Supervisor email - pmb20 [at] cam.ac.uk
Group name - Computational Cognition Group
Group website - https://bayslab.org
Group research interests - The Computational Cognition Group studies how our brains internally represent the external world, using methods from computational neuroscience and experimental cognitive psychology. We also collaborate with researchers using brain imaging, recording and stimulation, and with neuropsychologists who study cognitive aging, mental illness and neurological disorders. A major focus of the lab is on visual working memory. Our ability to recall details of what we have just seen is remarkably limited: we study how this core cognitive resource is distributed between elements of a visual scene to support behavioural goals. In the brain, information about our environment and our planned actions is encoded in the spiking activity of neurons. We develop models based on neural coding principles to identify mechanisms that are compatible with human perception and behaviour. We also have long-standing interests in efficient coding, sensorimotor prediction and motor learning.
Group methods - Computational modelling: probabilistic (Bayesian) inference, population coding and artifical neural network models. Extended reality (XR) technology. EEG frequency tagging including RIFT. Eye and body movement recording in naturalistic environments. Computer-based cognitive experiments, eye-tracking including gaze-contingent tasks.
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
1. Neural network models of transsaccadic integration in natural environments: this project would train artificial neural networks to solve a problem facing the brain in daily life, that of combining information about objects captured across different gaze fixations. Training data will be obtained from mobile eye-tracking in real-world environments, and the models will make predictions that can be tested by human psychophysics experiments in the lab.
2. Using EEG frequency tagging to index allocation of visual attention and investigate its role in working memory encoding. Rapid Invisible Frequency Tagging (RIFT) is a non-invasive method of tracking the processing of individuated visual objects in the human neural system over time. This project would combine RIFT with psychophysical methods and computational modelling to investigate when and how an attended object becomes a remembered object in the visual environment.
3. Studying adaptation in the human perceptual system with Extended Reality (XR) technology: this project would measure short-term changes in perceptual judgement induced by exposing participants to virtual environments with distorted visual statistics. Computational models will discriminate between changes in visual encoding versus decoding, and test competing accounts of how the visual system is optimized for natural environments.
Supervisor email - rb643 [at] cam.ac.uk
Lab website - www.neuroinformatics.science
Group research interests - The NeuroInformatics group is a computational group with a strong interest in studying lifespan brain health. A multitude of factors can affect our brain health from as early as pre-conception. These factors can pose great threats to the brain, leading to immense missed developmental potential, global disease burden and disability. We aim to tackle the diversity of challenges to studying brain health across the lifespan my using big data (both in terms of number of individuals, as well as in terms of numbers of features) and by developing novel approaches to integrating data across modalities and scales. In line with this goal our research program has three broad pillars: 1. Normative models of lifespan brain health: in this pillar we generate normative references for different brain features that can be measured with non-invasive brain imaging techniques such as MRI or CT. We also use these normative reference models to study deviations in clinical cohorts ranging from developmental and rare genetics disorders to conditions of accelerated ageing such as Alzheimer's and related dementias. See for an example: Bethlehem, Seidlitz, White et al. 2022, Nature. 2. Multi-scale integration: in this pillar we aim to integrate other data modalities with neuroimaging to gain a more complete understand of what it is that we are actually measuring with in-vivo neuroimaging techniques. This often included integration with genomics and transcriptomics. See for examples of this: Warrier et al. 2023, Nat. Gen. & Romero-Garcia, Warrier et al. 2019, Mol. Psychiatry. 3. Predictive applications: in this pillar we aim to develop novel machine learning approaches for risk prediction of ill brain health. See for an example: Azevedo et al. 2022 Medical Image Analysis
Group methods - Normative modelling - Computational modelling and machine learning - Neuroimaging (mainly MRI and functional connectivity) - Genetics and genomics - Software development
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
1. Imaging-genetics - integrating different data types at different scales is vital for a comprehensive understanding of brain health. We currently collaborate closely with Prof. Varun Warrier to integrate our large-scale imaging with genetics databases to both create a resource for the wider community but also to better understand the integrated relationships across brain phenotype and the biology underlying potential deviations in brain related phenotypes.
2. Normative models for atypical development (i.e., autism and adhd) - as we continue to improve our normative reference models there is an increasing need and interest to test the clinical or translational potential of these. While the group mainly focuses on testing the efficacy of these models in neurodevelopmental conditions such as autism and adhd, we also closely collaborate with a much wider network of researchers and clinicians to understand the translational potential in other clinical conditions.
3. Developing open tools for brain network analyses - with a strong interest in standardising approaches to quantify biological data we are building open workflow and tools for studying biological networks with a specific emphasis on network data derived from human in-vivo brain imaging.
4. Image segmentation and analysis - as we are dealing with more and bigger data we have several project underway to try and optimise processing pipelines for human in-vivo imaging. In addition, we are increasingly interested in integrating clinically acquired (as opposed to research grade) data and this requires processing adaptation and optimisation.
Supervisor email - sjblakemore [at] psychol.cam.ac.uk
Lab website - https://sites.google.com/site/blakemorelab/
Lab research interests - Brain development, social cognitive development and mental health in adolescence.
Lab methods - Experimental behavioural studies in the lab and in schools, structural MRI, functional MRI, eye-tracking, statistical modelling of developmental datasets.
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
The project will form part of a wider cohort study investigating microstructural brain development and social cognitive development in typically developing children and adolescents aged 8-18 years. The PhD project will involve analysing data from ultra-high-resolution MRI scans to investigate how brain microstructure relates to behavioural measures from experimental tasks and to mental health outcomes, and how this changes across age during adolescence.
Supervisor email - mb383 [at] cam.ac.uk
Lab website - https://www.psychol.cam.ac.uk/brain-language-and-bilingualism
Lab research interests - We are a cognitive neuroscience lab based in the Department of Psychology at the University of Cambridge. We aim to understand the cognitive and neural mechanisms that allow us to use and comprehend language; and to explore how these mechanisms may have evolved. We also aim to understand how our brains adapt to the requirements of learning and using more than one language.
Lab methods - Computerised Cognitive tasks; Neuroimaging (e.g., EEG, fMRI); Online studies
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
1. Neuro-cognitive foundations of combinatorial language function. Studying how the brain encodes this defining feature of human language; how this capacity might have emerged, and to what extent these processes differ across languages
2. The encoding of semantic and syntactic information in bilingualism. The demands of learning and using multiple languages modulate the way our neural system encodes perceptual signal. Does this extend to the processing of higher-level linguistic information?
3. Determinants of second language learning. How different variables and their interactions affect L2 learning and ‘mould’ an individual learner? Can this be used to personalise L2 teaching?
Supervisor email - lgc23 [at] cam.ac.uk
Lab website - https://scholar.google.co.uk/citations?user=JBJVQUIAAAAJ&hl=en
Lab research interests - 1. Evaluating cognitive capabilities in AI. 2. AI models of biological cognition
Lab methods - 1. Experimental 2. computational
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
Impact of inflammation on cognition, inflammation and memory development, AI models of infant cognition
Supervisor email - nsc22 [at] cam.ac.uk
Lab research interests - Cognition in humans and in non-human animals, especially corvids and cephalopods.
Lab methods - Experimental design to develop cognitive tests of behaviour, as well as theoretical work combining a variety of approaches from evolutionary biology, modelling, AI and philosophy
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
Corvid cognition. This is my top priority given that my corvid palace was saved from closure https://www.theguardian.com/environment/2022/jun/19/queen-of-corvids-the-scientist-fighting-to-save-the-worlds-brainiest-birds https://www.newscientist.com/article/2329991-cambridge-lab-for-clever-birds-saved-from-closure-by-public-donations/
I’m particularly interested in exploring aspects of mental time travel, self control and social cognition, and the use of magic effects to investigate constraints on cognition, i.e. blind spots in seeing and roadblocks in thinking. This work is conducted at the Sub-department of Animal Behaviour at Madingley, but there is also the opportunity to incorporate field work both in Madingley woods and further afield. Cephalopod cognition. I’m fascinated by cephalopods in general. Topics include idynamic camouflage and its relationship to both cognition and magic, as well as other aspects of cognition such as curiosity. This work is generally conducted at the MBL in Plymouth as we do not (yet) have a cephalopod facility in Cambridge. Comparative cognition. Questions about what are the critical comparisons in comparative cognition, from studies investigating similarities and differences in performance on tasks that tap into cognition in children and crows, to questions about convergent evolution in corvids, apes and cephalopods. The lab is genuinely interdisciplinary with additional studies on adult humans, as well as monkeys, elephants, parrots, dogs and dolphins, and transdisciplinary approaches and applications to cognition from philosophy to modelling and AI. Cultural cognition in humans. A relatively recent focus has been to compare the development in young children, and existence in adults, of cultural differences in cognition, from self control and future planning to Theory of Mind especially Level 2 perspective taking. So far these comparisons have focused on Individualistic and collectivist cultures, focusing on differences between UK and Chinese populations.
Supervisor email - jwd20 [at] cam.ac.uk
Group website - https://www.neuroscience.cam.ac.uk/directory/profile.php?jwd20
Group research interests - Behavioural and cognitive functions of limbic cortico-striatal circuitry and monoaminergic neurotransmitters. Translational research on the neurobiological and psychological mechanisms of behavioural traits (or endophenotypes) linked to developmental and stress-related disorders (e.g. drug addiction, ADHD, OCD, anxiety and depression).
Group methods - High resolution MRI (structural and functional); positron emission tomography; psychopharmacology; touchscreen-based behavioural tasks; in-vivo optogenetics; chemogenetics (DREADDs); in-vivo biosensors and neurochemistry; immunohistochemistry; computational modelling; electrophysiology
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
[1]. Early social stress (e.g. social deprivation) is known to have dramatic effects on the developing nervous system and often manifests as anxiety and other mood related disorders later in life. The JD group is interested in understanding the biological origins of so-called 'stress memories', the mechanisms underlying their persistence, and how knowing something about their underlying cause can help inform new treatments for mood related disorders in humans. To address these questions we use sophisticated behavioural tasks and procedures in rodents, longitudinal brain imaging, single cell RNA sequencing, and computational modelling.
[2] A further ongoing area of research involves the investigation of inhibitory microcircuits in visual perceptual learning. This specific form of learning is known to depend on the inhibitory neurotransmitter GABA but the precise mechanism is poorly understood. Using a range of convergent approaches, including MR spectroscopy to measure in-vivo GABA levels, touchscreen behavioural tasks, psychopharmacology, GABA biosensors, and intra-cortical drug delivery systems, we aim to provide a detailed understanding of the molecular and cellular mechanisms underlying visual perceptual learning. Such knowledge is relevant to everyday perceptual judgements and disorders such as autism and schizophrenia that implicate impairments in the development of inhibitory microcircuits.
[3] The JD group also a longstanding interest in the brain monoamine systems (dopamine, noradrenaline, serotonin) and uses state-of-the-art genetically engineered approaches to measure the release of monoamine neurotransmitters on rapid timescales with sub-second resolution. This technology is currently being used to understand the conditions that specifically recruit each of the monoamine systems. We are especially interested in the concept of error prediction coding and how anxiety traits affect the recruitment of different monoamine systems during situations where learning rates vary depending on the probability of rewarded outcomes. This research is relevant to depression and anxiety related disorders such as GAD and OCD.
[4] A final general area of interest involves research on the brain and psychological mechanisms of individual vulnerability for drug addiction. We are especially interested in addiction relevant traits (impulsivity, anxiety) and employ longitudinal brain imaging, genomics, circuit level investigations, and computational neuroscience to reveal novel mechanisms underlying individual predisposition for addiction.
Supervisor email - gjd1000 [at] cam.ac.uk
Lab website - https://www.viscog.psychol.cam.ac.uk/
Lab research interests - Visual Cognition and Attention
Lab methods - Human Performance, Eyetracking
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
Visual Attention and Awareness. A primary focus of the lab is to develop new behavioural measures to profile visual awareness during complex tasks. Findings from this work have motivated novel security screening strategies in our applied work. In collaboration, we are currently expanding this work to include M/EEG correlates. Social Cognition, with special emphasis on Gaze Perception A second focus concerns rapid appraisal of social information by human observers, especially in relation to eye gaze. At one level, another person’s eyes are just like other visual stimuli, at another, they indicate the presence of another mind and are seeing as well as being seen. Our previous and current work investigates how high level knowledge that a person can see influences our perception of eyes and responses to them.
Supervisor email - lhd26 [at] cam.ac.uk
Lab website - https://www.psychol.cam.ac.uk/polpsych
Lab research interests - Political Psychology, Political Behaviour, Morality, Polarization, Comparative Politics, Behaviour Change
Lab methods - Surveys, Experiments, Computational Modelling
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
Computational Political Psychology: Using clustering and dimensionality reduction techniques to understand how citizens political preferences are structured, and how (or whether) citizens are genuinely organized into distinct ideological groups. Data driven dimensionality approaches are particularly useful for interrogating the structure of political attitudes, for example how well political attitudes fall along one axis (left right), or are better captured by multiple different axes (economic and social). Clustering approaches (K-Means, Latent Class Analysis) are particularly useful for understanding the extent to which citizens are clustered into coherently opposed groups. Across both of these approaches we are keen to extend the focus of political psychology outside of the US and Europe, and test the extent to which different dimensionality structures might be needed to account for the structure of political attitudes in different countries. Similarly with clustering techniques, we are interested in exploring whether different political systems (such as first past the post or proportional representation) result in different levels forms of clustering.
Experimental Political Psychology: A lot of insights into political psychology rely on a correlational analysis of the beliefs, personality types, moral values or cognitive profiles that are associated with certain forms of political behaviour. As a political psychology lab, we are interested in testing the causal power of those associations through carefully designed experiments. This could take the form of a message framing experiment, where support for a given policy agenda (such as climate change) could be framed in different values (equality vs patriotism), to test whether people have fixed views on a particular policy or are more influenced by the way in which that policy is framed.
Supervisor email - ch288 [at] cam.ac.uk
Lab website - https://www.cfr.cam.ac.uk/our-labs. See also https://newn.cam.ac.uk/person/claire-hughes
Lab research interests - executive functions, theory of mind, school readiness, young children's family relationships with parents, siblings, grandparents, cultural influences
Lab methods - experimental child assessments, video and transcript-based coding of children's social interactions, longitudinal and cross cultural designs
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
1) Starting school Studies of school readiness typically focus on child skills, overlooking crucial individual differences in the support children receive from families and schools. Adopting a broader perspective is crucial for understanding both emotion-based school avoidance and the experiences of children with special educational needs and disabilities (SEND). The dimensions of time and place are also important. Rather than a narrow focus on Reception Year, a temporally extended approach to the transition to school is needed, as Year 1 brings a rapid increases academic, behavioural and social demands on children that are often overlooked. Likewise, cultural differences in pedagogical practices can be striking, and may be illuminating for identifying key ingredients of early school success. My team is also developing resources for families that we hope will have practical value – assessing the impact of these resources is an obvious direction for PhD work.
2) Children’s family relationships One (possibly unintended) consequence of the prominence of attachment theory is a narrow focus on mother-child relationships. Again, adopting an international perspective can be valuable for gaining a clear understanding of similarities and contrasts in family life across different contexts, and the impact of family on children’s development and adjustment. Adopting family systems theory, my team are conducting studies that seek to widen the scope of this work, by exploring children’s relationships with fathers, siblings and grandparents, working with different age groups and families from different countries. Currently, our grandparent study only includes grandparents – I’d welcome PhD students interested in developing this by adopting a multi-informant approach to integrate views from children, parents and grandparents.
3) Executive functions and theory of mind Common threads across all my work are individual differences and developmental changes in children’s self-regulatory skills and social cognition. Our recent cross-cultural findings challenge the expected East-West contrast in executive function, which may hinge on contextual effects, as unlike the school / lab settings adopted in most prior studies, we used remote methods to assess children in a home context. I’d welcome PhD students interested in developing this by assessing children’s executive functions and theory-of-mind skills in different contexts and settings.
Supervisor email - zk240 [at] cam.ac.uk
Lab website - https://www.abg.psychol.cam.ac.uk
Lab research interests - Our experimental work aims to understand the role of lifelong learning and brain plasticity in enabling humans of all ages to translate sensory experience into adaptive behaviours. Our research programme bridges work across scales (local circuits, global networks) and species (humans, animals) to uncover the neurocomputations that support learning and brain plasticity. Our computational work aims to develop AI-guided models for understanding the brain network dynamics that support adaptive behaviour and predictive models of brain and mental health. Our work has translational impact in the early diagnosis and design of personalised interventions in brain and mental health focusing on neurodegenerative (i.e. dementia) and neurodevelopmental disorders.
Lab methods - ultra high-field structural, functional and neurochemical brain imaging; behavioural and cognitive testing computational modeling; AI and machine learning; electrophysiology (EEG), interventional (TMS, tDCS)
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
Cognitive computational neuroimaging studies of learning and brain plasticity: Our studies combine ultra-high field brain imaging (7T fMRI, MR Spectroscopy), electrophysiology (EEG), interventional (TMS, tDCS) and neurocomputational (machine learning, reinforcement learning) approaches to understand the network dynamics that support learning and brain plasticity. AI and Neuroinformatics: We develop and translate AI-guided tools for a) understanding brain processes underlying cognition (e.g. learning and brain plasticity), b) early detection of brain and mental health disorders to inform clinical practice (healthcare, clinical trials). Our research involves working on research cohort and clinical data, developing machine learning models to synthesise biological (brain imaging, genetic) cognitive and epidemiological data, validating AI-guided tools in clinical data, translating these tools for adoption in healthcare and industry settings.
Supervisor email - rl337 [at] cam.ac.uk
Lab website - www.lawsonlab.co.uk
Lab research interests - The Prediction and learning (PaL) lab are a cognitive computational neuroscience lab with interests in how humans learn to make predictions in an uncertain world. Uncertainty is a common feature of everyday life that affects perception and decision-making – whether we’re trying to predict which political party will win the next general election or struggling to navigate our way home on a foggy day. Our brain has specialized mechanisms for representing and responding to uncertainty, yet people radically differ in how they cope with the unknown. In the PaL Lab we study these processes in adults with and without neuropsychiatric conditions (e.g., anxiety, depression, autism) and in development, in order to understand how these fundamental mechanisms, emerge from early infancy to shape the adults that we are today.
Lab methods - Computerised Cognitive tasks. Computational modelling (e.g. reinforcement and Bayesian learning models). Psychopharmacology (e.g. SSRIs and other neuromodulators). Neuroimaging (e.g. magnetic resonance imaging, near infrared spectroscopy). Physiology (e.g. heart rate, skin conductance, pupillometry). Eye-tracking. Online studies
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
1. The role of uncertainty in social processing (e.g., ambiguous facial expressions) - Are the difficulties with social processing reported across many psychiatric disorders related to ambiguity in how we represent facial expressions, and are these difficulties affected by common psychiatric medication such as SSRIs? Is social uncertainty processed in the same way as uncertainty in other cognitive domains?
2. Translation of uncertainty tasks across species (humans and rodents) - Deeper understanding pf the mechanisms of uncertainty processing requires forward and back-translation of research across humans and animal models that are commonly used in medical research (e.g. rodents). Projects in this area would be co-supervised by Professor Jeff Dalley.
3. Learning under uncertainty in infancy - Studying how infants learn and adapt to uncertainty required novel neuroimaging tools that are suitable for little people who struggle to keep still. The lab has acquired a cutting-edge Diffuse Optimal Tomography (DOT) system and are interested in PhD students keen to use this method in developmental studies.
These research topics fall within the remit of Pinsent-Darwin ("Mental Disorders") research projects.
Supervisor email - sl868 [at] cam.ac.uk
Lab website - http://www.pipkinstudy.com/ and http://Globalfnirs.org
Lab research interests - The Lloyd-Fox lab studies how early brain and cognitive development is shaped by biological, social, and environmental experiences, before and after birth, with the goal of improving child development and mental health outcomes through innovative neuroscience and community-partnered research.
The Perinatal Imaging in Partnership with Families (PIPKIN) Research Group partner with parents and expectant parents to shed light on the earliest experiences in a person's life, from the womb, through the first days following birth and formative social interactions during the first months of life. Once a common misconception – that newborns are passive and lacking in capacity – we harness recent technological advances, including 4D ultrasound, wearable optical imaging (fNIRS/DOT) and EEG, heart rate monitors and video and audio recording devices to explore the amazing abilities that humans possess both during fetal and early infant development. We explore how fundamental attention and social mechanisms emerge during pre to postnatal life and how the world around us shapes our behaviours and early brain development. The Brain Imaging in Global Health (BRIGHT) Research Group comprises a team of researchers from the University of Cambridge, UCL, the Medical Research Council Gambia at LSHTM, KCL and Birkbeck University of London, who use longitudinal study designs to explore how early infant behavioural, cognitive and brain development is shaped by the contextual factors that surround us. 1 in every 2 children worldwide are thought to live in poverty. We explore how the effects of living in a low-resource context in The Gambia with increased likelihood of environmental difficulties such as under nutrition and increased risk of disease, may impact early development and shape who we are. We also explore how enriched contextual factors such as multigenerational, multi-caregiver families may boost early development, learning from contexts that are largely under-represented in developmental science.
Lab methods - Neuroimaging (i.e. functional near infrared spectroscopy - fNIRS, electroencephalography - EEG); Computerised cognitive tasks; Physiology (i.e. heart rate); Eye-tracking; Online studies; Longitudinal modelling; Family social interactions; Behavioural cognitive measures
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
1. Harnessing knowledge from developmental neuroimaging to develop science-based interventions: Whether in the UK or at a global level, socially, culturally or financially disadvantaged groups – those most at risk for experiencing socio-economic and health challenges - are far less likely to participate in, and therefore benefit from, research. Empowering science-based parental education on brain development and non-judgemental support translate into increased knowledge about positive child caregiving practices, improved perinatal mental health and the consequent ability to give children the best possible start in life.
2. Build on recent findings: i.e. poverty-associated physiological factors (maternal pro-inflammatory diet and maternal psychological stress/MH) contribute to infant adaptive brain response profiles/ brain network organisation to move towards biomarker identification. Aiming to influence academic, governmental health and education guidelines we will implement modelling pathways to validate a “fingerprint” combination of brain and cognitive markers that predict the contribution of enriching and adversity factors to individual diversity.
3. Understanding enriched family contexts in Sub-Saharan Africa: The BRIGHT Study use longitudinal study designs to explore how early infant behavioural, cognitive and brain development is shaped by the contextual factors that surround us. Hundreds of videos of parent – infant interactions, family interviews, audio data from home recordings and a range of demographic and family caregiving data has been collected in rural Gambia over the past decade. There is an opportunity to explore alongside researchers in The Gambia how enriched contextual factors such as multigenerational, multi-caregiver families may boost early development. Learning from contexts that are largely under-represented in developmental science will allow us to better understand how our world shapes who we are.
Supervisor email - jjr51 [at] cam.ac.uk
Lab website - https://www.psychol.cam.ac.uk/node/8647
Lab research interests - Why do we believe some things but not others? Why do we share information about ourselves and the groups we belong to, or groups we dislike? What are the effects of information and propaganda during wartime? How do communication technologies shape how we feel, think, and behave? What makes interventions to address policy challenges effective? And how do we measure these things, with what kind of data? These are some of the overarching questions that the Influence and Technology Lab seeks to answer. To do so, we rely on the most advanced methods in the social and computational sciences, by building on methodological and theoretical frameworks from computer science, psychology, and area studies. The lab has a strong cross-cultural focus, collecting data and conducting experiments in many countries around the world and combining methodological rigour with an in-depth understanding of the societies under study.
Lab group methods - Computational modelling, Machine learning and AI, Agent-Based Modelling, Surveys, Field Studies, Psychometrics
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
1) The digital manipulation economy: inauthentic content is rife in online environments, from fake likes to sophisticated bot-driven propaganda campaigns. We are interested in understanding the marketplace that sells inauthentic activity, and how we can make its products and services more expensive.
2) The effects of (information) warfare: modern conflict is kinetic as well as informational. We are interested in understanding how war and information intersect, both during and after (military) intergroup conflict.
3) The social science of generative AI: As (generative) AI tools become part of our daily routines, understanding how they interact with humans is critical. We are interested in understanding how humans and AI interact, and the downstream effects of these interactions. We are especially interested in how humans interact with multiple AI agents, for example on social media.
4) The political psychology of social media: Why we consume and share content in online environments, and how doing so impacts beliefs, attitudes, and behaviours, is an important scientific as well as policy question. We want to understand these phenomena in countries around the world, and to understand the causal (psychological) mechanisms that drive people’s behaviour in social networks.
5) Intervention and implementation science: Addressing societal challenges is a complex task. We are interested in understanding what makes psychological and behavioural interventions (e.g., against polarisation, misinformation, or other societal phenomena) effective rather than merely efficacious (effectively asking how we can take these interventions from the petri dish to the pharmacy) and how to predict interventions’ impact in the real world.
For more information, see: https://www.psychol.cam.ac.uk/influence-and-technology-lab/research
Supervisor email - jss30 [at] cam.ac.uk
Lab website - http://www.memlab.psychol.cam.ac.uk
Lab research interests - Our research investigates the cognitive and brain mechanisms of human memory, focusing particularly on the subjective experience of remembering and how we use mental experiences to make sense of the world. This work involves inter-relating cognitive hypotheses with evidence from functional neuroimaging of healthy volunteers and from examining the effects of neurological and psychiatric disorders, and normal aging, on memory abilities. We then work to realise the impact of our research by translating the findings into training interventions that can help older adults and others to apply effective encoding and retrieval strategies in everyday life to enhance independence and wellbeing.
Lab methods - Research in the Memory Laboratory uses a variety of approaches (behavioural, neuroimaging, electrophysiology, clinical studies, brain stimulation, cognitive remediation) to dissect the processes that give rise to the multifaceted properties of subjective experience.
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
The ability to remember personally experienced events in vivid, multisensory detail makes an immensely important contribution to everyday life. Such recollection is considered to involve reactivating sensory and perceptual details of an event, and the thoughts and feelings we had at the time, and integrating them into a conscious representation during retrieval. It makes possible a number of critical decision making abilities, such as distinguishing real experiences from those we might have imagined or been told about. However, the cognitive and neural mechanisms that underlie the subjective experience of remembering remain unresolved. The aim of PhD projects in the lab will be to help develop a detailed neurocognitive characterization of subjective memory, to better understand the way it may be impaired in health and disease, and to develop rehabilitation strategies to help those who may have reduced ability to re-experience the past.
Supervisor email - aw316 [at] cam.ac.uk
Lab website - www.woolgarlab.org
Lab research interests - We study the neural basis for cognitive control, underpinning the incredible human capacity for diverse and flexible behaviour. Our research uses multivariate analysis of different types of neuroimaging data (fMRI, E/MEG) often in combination with non-invasive brain stimulation (TMS-EEG, TMS-fMRI), to study how information is represented, exchanged, and transformed between regions of the human brain. We focus on frontoparietal “multiple-demand” (MD) brain regions which appear to prioritise coding of task-relevant information, providing a neural basis for selective attention. We study the temporal dynamics and causal interactions of information coding in and between this and other brain networks, and seek to understand the links between neural processing and behaviour. Key applications of our work include predicting lapses of attention in tasks inspired by air and rail traffic monitors, and using our methods to study hidden cognitive ability in non-speaking autistic children.
Lab methods - Non-invasive human neuroimaging (fMRI, MEG, EEG) and neurostimulation (TMS), their combinations, and advanced analytics (computational approaches including multivariate pattern analyses MVPA)
In addition to PhD proposals on topics that the candidate has devised themselves, I am currently welcoming PhD proposals related to the following topic(s):
1. Cross-species study of selection and representation of sensory information, for example in collaboration with Dr. Poort or Dr. Beltramo (Department of Physiology, Development and Neuroscience)
2. Using non-invasive neuroimaging to track disruption and compensation to attentional processing after brain injury (e.g., Stroke)
3. Novel (including EEG-based) approaches to assessing receptive language in non-speaking autistic individuals