environMENTAL open position

environMENTAL is looking for ambitious new people. Find out about all open positions.

Post-doctoral research associate (Radboud University Medical Center, Netherlands)

Vacancy for an excellent post-doctoral research associate focusing on the development and application of advanced statistical and machine learning methods for the analysis of clinical neuroimaging data and other data modalities.The successful applicants will develop and apply a range of techniques, spanning both classical statistical approaches (e.g. classical and Bayesian analysis methods) and machine learning methods (e.g. kernel methods, matrix factorization techniques, supervised/unsupervised and deep learning) to neuroimaging and other clinical data. The successful applicants will also then produce software tools to enable other researchers to take advantage of the innovations produced in these projects. The project is highly interdisciplinary and integrates machine learning and statistics with cognitive neuroimaging and clinical neuroscience. Therefore, a numerate background and programming skills are essential and a keen interest in cognitive or clinical neuroscience is highly desirable.


Postdoc (King’s College London, UK)

Applications are invited for a talented, enthusiastic and highly motivated postdoc to work with Professor Sylvane Desrivières in the Social, Genetic and Developmental Psychiatry (SGDP) Centre at the Institute of Psychiatry, Psychology and Neuroscience, King’s College London.
The successful candidate will be part of the ‘omics team, which aims to characterize molecular and neurobiological mechanisms underlying mental illness and identify multimodal biomarker profiles of disease risk and resilience.
The work involves applying comprehensive bioinformatics and biostatistical analyses to ‘omics data (genetics, epigenetics, transcriptomics, proteomics) collected from well-characterised longitudinal adolescent cohorts assessed for common mental illness (depression, anxiety, eating disorders). This multi-level -omics data will be used for integrative analyses with other data layers (e.g. brain imaging, neuropsychological and neurocognitive assessments).
The successful candidate will have a PhD in bioinformatics, computer science or a related discipline (biostatistics, biomedical engineering, applied math) or genetics.  Excellent scientific writing skills and a good publication record are highly desired.


Research Worker (King’s College London, UK)

Applications are invited for a talented, enthusiastic and highly motivated to join Research Worker Professor Sylvane Desrivières’ team at the Institute of Psychiatry, Psychology and Neuroscience at King’s College London.
The successful applicant will work on the IMAGEN, STRATIFY and ESTRA studies, aimed at early detection and stratification of mental illnesses in young people. He/she will coordinate and execute recruitment/assessment of study participants, using a range of neuropsychological and neurocognitive tasks.
The position provides excellent opportunities for an ambitious individual to develop unique skills and expertise in clinical neuroscience. This post is also a unique opportunity to work with a worldwide network of collaborators and develop innovative research using cutting-edge
The successful candidate will have a degree in psychology, psychiatry , neuroscience or equivalent. Willingness to engage with patients and other service users in research and strong interpersonal skills are expected.


Data Engineer (Charité Berlin – Paris based)

We are looking for a motivated data engineer to join our team at the Centre for Population Neuroscience and Stratified Medicine (PONS) at Charité Universitaetsmedizin Berlin. The position will be located at Neurospin at Paris-Saclay. The main task is to maintain the IMAGEN (https://imagen-project.org/) and STRATIFY (https://stratify-project.org/) studies database, which is hosted at Neurospin. IMAGEN and STRATIFY are European research projects examining how biological, psychological, and environmental factors during adolescence and young adulthood may influence brain development and mental health. Using brain imaging and genetics, the project will help develop prevention strategies and improved therapies for mental health disorders in the future.

The database contains appr. 20 TB if clinical, genetic and neuroimaging data from a cohort of 2,400 participants, collected over 4 time points between 2010 and 2020, in 8 acquisition centres over 4 European countries. We have stored the data in files and strive to follow our domain’s current standards with respect to file organization and format.