Postdoctoral Fellow / Research Scientist (Ph.D.) in Human Neural Circuit Physiology
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Faculty of Arts and Sciences
Boston, MA (In Person)
$76,477 Salary, Full-Time
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Job Description
Position
Details
Title Postdoctoral Fellow / Research Scientist (Ph.D.) in Human Neural Circuit Physiology
School Faculty of Arts and Sciences
Department/Area Stem Cell and Regenerative Biology
Position Description The laboratory of Prof. Paola Arlotta invites applications for a Ph.D.-level Postdoctoral Fellow or Research Scientist with strong expertise in systems-level electrophysiology and neural data science. The successful candidate will investigate human neural circuit physiology and neuronal dynamics in human brain organoids, with a focus on CNS disorders such as Autism Spectrum Disorder (ASD).
The Arlotta Lab develops and applies human cortical organoid models to understand principles of human cortical development and how they are perturbed in neurodevelopmental and neuropsychiatric disease. This position will center on high-throughput functional interrogation of human neural circuits and on building new experimental and analytical pipelines to link cellular and circuit phenotypes to genetic risk.
Key Responsibilities
- Design and execute experiments to characterize single-cell and network-level activity in human cortical organoids and related human in vitro systems.
- Lead the implementation and optimization of high-throughput functional platforms, including: o Single-unit extracellular recordings (e.g., high-density MEA systems, neural probes) o Calcium and voltage-sensitive dye imaging for large-scale population dynamics
- Develop and integrate novel, cutting-edge technologies for functional circuit analysis; independently evaluate, set up, and optimize new hardware and software platforms.
- Build and maintain robust data analysis pipelines for large-scale electrophysiological and imaging datasets, including spike sorting, network analysis, and state/dynamics characterization.
- Collaborate with lab members generating organoids from neurotypical and ASD-associated genetic backgrounds to identify convergent and divergent network phenotypes.
- Present results in internal and external meetings, contribute to manuscripts and grant proposals, and help mentor students and research assistants.
ABOUT THE LAB
We encourage applicants to read more about our scientific goals on our lab website. In addition, the Arlotta lab is actively working to become an equitable and inclusive community. The lab recognizes the inequity and bias within the academic community and is dedicated to our continuous self-education and activism in these areas. Future members are strongly encouraged to be active participants in these endeavors as part of their scientific career. Basic Qualifications Required Qualifications- Ph.D. in Neuroscience, Biomedical Engineering, Physics, Computer Science, or a related quantitative field.
- Deep expertise in electrophysiology signal analysis, data science, and programming, demonstrated by publications and/or software tools, including: o Analysis of extracellular recordings (single-unit and multi-unit activity, spike sorting, LFP, synchrony, connectivity, oscillations) o Quantitative analysis of network activity from MEA and/or imaging o Proficiency in Python, MATLAB, or similar languages for data processing, statistics, and visualization.
- Substantial hands-on experience with systems neuroscience methods, such as: o High-density MEA recordings or other multi-site extracellular recording platforms o Calcium imaging and/or voltage-sensitive dye imaging for neuronal population dynamics o Whole-cell patch-clamp recordings o Synaptic physiology (evoked and spontaneous synaptic potentials, plasticity paradigms)
- Demonstrated ability to independently design, troubleshoot, and execute experiments and to manage complex datasets.
- Strong written and oral communication skills and a record of peer-reviewed publications commensurate with career stage. Additional Qualifications Preferred Qualifications
- Experience with human iPSC-derived neurons, brain organoids, or brain slices.
- Familiarity with modern spike sorting toolkits, machine learning or statistical modeling of neural data, and reproducible code practices (version control, documentation).
- Background in neurodevelopmental disorders, circuit neuroscience, or ASD-related research.
- Demonstrated interest in combining electrophysiology and imaging with single-cell genomics, spatial transcriptomics, or computational modeling.
- Proven ability and enthusiasm to evaluate, adopt, and innovate new experimental technologies (e.
- ).
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