Stress, attachment, and resilience mice and humans

Offer Description

Why do some individuals remain resilient in the face of adversity, while others experience lasting emotional, cognitive, or physiological consequences of stress? What makes close relationships a powerful source of protection? And how can insights from basic neuroscience inform our understanding of resilience in families?
This PhD project offers a unique opportunity to address these questions within an ambitious translational research programme that bridges animal and human research. The overarching aim is to uncover the mechanisms through which secure attachment promotes resilience and buffers the impact of stress, from controlled experimental models in mice to complex family interactions in humans.
The project consists of two complementary research lines.
The first research line builds on an established collaboration between the laboratories of Prof. Rudi D'Hooge and Prof. Guy Bosmans. Using a mouse model, this programme investigates the cognitive consequences of chemotherapy treatment and the mechanisms that explain why some individuals show greater resilience than others. Building on this ongoing work, the PhD candidate will examine whether attachment-related processes can serve as protective factors that buffer the detrimental effects of stress associated with cancer treatment.

This line of research offers a unique opportunity to connect attachment theory with cutting‑edge behavioural neuroscience and experimental models of stress resilience.
The second research line focuses on an exceptionally rich human dataset collected in families with school‑aged children. The project includes triadic data from mothers, fathers, and children, who participated in a series of individually and jointly administered stress‑inducing laboratory tasks. The available dataset integrates multiple levels of analysis, including attachment representations, behavioural observations, psycho-physiological responses, hormonal markers, epigenetic measures, emotional functioning, and cognitive processes.

Because data collection has been completed, the PhD candidate can immediately focus on developing and testing innovative research questions.
Using these unique data, the candidate will investigate how secure attachment within families contributes to resilience under stress, how parents and children mutually influence each other's responses during stressful situations, and whether resilience is transmitted across generations through attachment‑related processes. Particular attention will be paid to triadic family dynamics, moving beyond traditional parent‑child dyads to understand how mothers, fathers, and children together create a relational context that either amplifies or buffers stress.

The project also offers opportunities to examine biological and psychological pathways linking attachment, stress regulation, and resilience across generations.
Together, these complementary research lines provide an exceptional opportunity to integrate insights from behavioural neuroscience, developmental psychology, attachment theory, family research, and psychobiology. By combining controlled experimental animal research with multimethod family data, the project aims to advance our understanding of one of the most fundamental questions in mental health research: how supportive relationships protect individuals from the harmful effects of stress throughout development.

• Holds (or will soon obtain) a​Master's degree
  in​Psychology, Educational Sciences (Orthopedagogy), Biomedical Sciences, Neuroscience
  , or another relevant discipline.
• Has a strong interest in interdisciplinary research bridging​clinical psychology, developmental science, and behavioural neuroscience
  .
• Is enthusiastic about working with​both animal and human research
  and is willing to actively participate in data collection involving​mouse models
  as well as​children and families
  .
• Is eager to learn and apply a broad range of research methods, including behavioural, psycho-physiological, hormonal, and molecular approaches.
• Has an affinity for quantitative research methods and data analysis (experience with statistical software such as R, SPSS, or…