Postdoctoral Position: Data Science in Neuroscience

The EPFL Laboratory of Behavioral Genetics is seeking a highly motivated and skilled postdoctoral researcher to contribute to groundbreaking data-driven research in neuroscience. The successful candidate will play a central role in advancing our understanding of human behavior, stress, and motivation by applying advanced analytical techniques to rich and multidimensional datasets. These include data from cutting-edge Virtual Reality (VR) experiments, physiological assessments (e.g., SNS, hormonal markers, and neurometabolism), behavioral metrics, and neuroimaging. This position is ideal for a data scientist eager to harness these diverse datasets to drive innovative insights and make significant contributions to ongoing and future projects in the lab., The successful candidate will join an interdisciplinary team working on innovative projects that leverage VR scenarios and behavioral paradigms to study human stress, anxiety, and motivated behavior. The work involves analyzing diverse datasets, including behavioral responses, autonomic nervous system (SNS) and hormonal data, blood biomarkers, metabolic data, and fMRI outputs. This position provides an exceptional opportunity to apply and further develop expertise in advanced statistical and computational methods to uncover the neural and physiological mechanisms driving human behavior. The position will benefit from EPFL's strong computational expertise and collaborative opportunities, with potential for synergy with leading data science groups on campus., * Analyze large, multidimensional datasets, integrating behavioral, physiological, and imaging data (e.g., SNS, hormonal markers, metabolic profiles).

• Develop and apply data science tools and methodologies, including machine learning and advanced statistical modeling, to derive insights from complex datasets.
• Collaborate on the design of VR-based and other behavioral testing paradigms, as well as the analysis of the resulting data, to investigate stress, anxiety, and motivation.
• Investigate relationships between stress physiology, motivated behavior, metabolic markers and neural activity, identifying key mechanisms and biomarkers.
• Prepare high-quality manuscripts and present findings at international conferences.
• Supervise and mentor students and contribute to the collaborative lab environment.

• Ph.D. in a Data Science, Computer Science, Statistics, Biomedical Engineering, or a related field with a strong focus on data analysis
• Demonstrated expertise in analyzing complex, multidimensional datasets, including physiological signals, behavioral metrics, and imaging data.
• Strong programming skills in relevant languages (e.g., Python, R) and proficiency with statistical and machine learning frameworks.
• Experience in applying data science methods to areas such as stress physiology, motivated behavior, neuroimaging, or metabolic analyses is an asset.
• A track record of high-quality peer-reviewed publications.
• Excellent interpersonal and communication skills, with the ability to work both independently and collaboratively in an interdisciplinary research environment., * A cover letter detailing your research background, technical skills, and fit for the position.
• A detailed curriculum vitae (CV) including a full list of publications.
• Contact information for three professional references.

EPFL offers a dynamic and collaborative research environment with world-class facilities and a commitment to innovation and excellence. The Laboratory of Behavioral Genetics, embedded within the Brain Mind Institute, is at the forefront of research on stress, anxiety and motivation, providing a stimulating setting for scientific growth and impactful discovery. This position also benefits from the computational expertise and collaborative culture at EPFL, fostering opportunities for synergy with leading data science and neuroscience groups on campus. We are dedicated to fostering diversity and encourage applications from individuals of all backgrounds. Join us in advancing the boundaries of neuroscience and data science to uncover the complexities of human behavior. We look forward to your application!