DSP Postdoctoral Fellow

Description & Requirements

We are seeking a highly motivated Postdoctoral Fellow to join our interdisciplinary team focused on advancing neuroscience research through innovative multimodal data integration techniques.

This position offers a unique opportunity to contribute to cutting-edge projects aimed at resolving challenges in cell type classification, scalability of brain mapping methods, and establishing a cross-modality cloud data ecosystem for larger neuroscience communities.

Responsibilities : Developing Data-Driven Integration Techniques : Collaborate with team members to design and implement novel data-driven integration techniques for resolving inconsistencies in cell type classification across multiple modalities.

Utilize advanced machine learning algorithms to establish objective criteria for cell classification based on similarity across data sets.

Enhancing Scalability of Brain Mapping Methods : Contribute to the development of computational algorithms to infer unobserved features of single neurons using sparse multimodal measurements.

Implement self-supervised machine learning techniques to scale up efforts in brain cell mapping, leveraging both multimodal and single-modal data sources.

Creating a Cross-Modality Cloud Data Ecosystem : Work towards establishing a cloud-based infrastructure for multimodal neuroscience data analysis.

Collaborate with project partners to integrate computational resources with existing BRAIN Initiative repositories, enabling broader access to data and analysis pipelines across institutes.

Innovation and Methodological Development : Stay abreast of the latest advancements in machine learning, neuroscience, and data integration methodologies.

Contribute to the development of innovative approaches for multimodal data analysis and dissemination within the neuroscience community.

Collaboration and Outreach : Engage in collaborative efforts with researchers from diverse backgrounds to promote objective multimodal analysis methodologies.

Participate in outreach activities aimed at sharing results, methodologies, and resources with the broader neuroscience community.

Qualifications : A Ph.D. in Neuroscience, Computer Science, Electrical Engineering, or a related field. Strong background in machine learning, statistics, and computational neuroscience.

Experience with analyzing multimodal data sets, preferably in the context of neuroscience research. Proficiency in programming languages such as Python, MATLAB, or R.

Excellent communication and collaboration skills. Ability to work independently and as part of a team in a dynamic research environment.

Prior experience with cloud computing platforms and data repositories is desirable. Benefits : Opportunity to work on cutting-edge projects at the intersection of neuroscience and machine learning.

Collaborative and supportive research environment with access to state-of-the-art resources. Competitive salary and benefits package commensurate with qualifications and experience.

Potential for professional development and opportunities for career advancement. If you are passionate about advancing our understanding of the brain through innovative data integration techniques and are excited to tackle challenges at the forefront of neuroscience research, we encourage you to apply for this position.

Join us in our mission to create a common ground for collaborative neuroscience research and contribute to the development of transformative methodologies for studying the brain.