Wu Tsai Postdoctoral Fellowship at Yale - For scientists interested in interdisciplinary neuroscience

Come join a community dedicated to understanding the mind and cognition through integration across disciplines, organisms, and scales.

The Wu Tsai Postdoctoral Fellowship program at Yale seeks scientists who are excited about frontiers in interdisciplinary neuroscience and who represent a diversity of identities, including those from historically underrepresented backgrounds in science.

Apply to one of four priority co-mentored projects, carefully selected for their science and inclusive and supportive training environments, or submit an application to our open track.

Fellows receive:

  • Competitive stipend ($60,000), health benefits, and discretionary training funds for a maximum of three years, upon annual review
  • Cohort-based professional development and community-building activities
  • Access to cutting-edge facilities at the new Wu Tsai Institute
  • PhD degree or equivalent, awarded within past three years
  • Track record of discoveries and demonstrated level of scientific independence appropriate for a beginning postdoc
  • Self-identifying as being a member of a group underrepresented in science and/or demonstrated commitment to fostering diversity, equity, and inclusion.
  • Interdisciplinary orientation
  • International applicants welcome
  • Current Yale postdocs and PhD students are not eligible to apply

Deadline for applications is August 15.
To apply and for more info see: https://bit.ly/WTIPostdocFellows

Priority areas include:

  • Uncovering the molecular basis of neuroticism, a fundamental personality trait - Explore the effect neuroticism-associated DNA variants on gene expression and develop massively parallel reporter assays to test effects on neural systems. Applicants should have expertise in stem cell biology, neuroscience, massively parallel reporter assays, high-throughput CRISPR genomic manipulations, and/or statistical genetics and epigenetics, and be interested in bridging computational and experimental approaches.
  • Learning the language of thought: machine learning to infer spatiotemporal rules of cognition from mesoscopic calcium imaging data – Infer patterns in brain activity by applying natural language processing to large-scale calcium imaging datasets from awake behaving mice. A background in computer science, applied math, computational biology, machine learning, and experience working with large datasets is preferred. A strong interest (but not necessarily experience) in neuroscience is required.
  • Toward the neural bases of cooperative social interactions through a unique primate model - Unravel the prefrontal mechanisms underlying cooperation using a unique freely behaving marmoset model. Candidates should have experience in at least two of the following areas: non-human primate behavior, electrophysiology, or computational analysis.
  • The functional genomics of human cognition: from molecular and cellular processes though large-scale brain networks - Explore how genetic variation results in cognitive and behavioral differences by developing processes to link data across genetics, genomics, neuroimaging, and behavioral domains. Applicants should have demonstrated expertise in clinical, cognitive, translational, or network neuroscience, computational biology, or genetics.
  • Open Area – If you are an early-career researcher interested in foundational studies of the mind, but do not fit the priority areas above, we still welcome your application. We are particularly interested in candidates from underrepresented backgrounds with expertise in molecular and cellular neuroscience, systems and cognitive neuroscience, computational neuroscience, psychology, data science, artificial intelligence, biomedical engineering, brain-machine interfaces, and neuroethology. Applications in this track will be considered depending on mentor and funding availability.