Duties: The Computational Memory Lab at the University of Pennsylvania (memory.psych.upenn.edu) seeks to hire a scientific programmer who is eager to work with a team of cognitive scientists, neuroscientists, and engineers on technologies that employ direct brain recordings and stimulation as a research tool and a potential therapy to treat memory disorders. This research is being carried out in the DARPA-funded Restoring Active Memory program and National Institutes of Health grants to understand the neural correlates of human spatial and episodic memory. This position is a great opportunity for a talented developer to gain substantial exposure to the emerging field of neurostimulation. The selected applicant will develop and maintain technical computing software (including a real-time neuro-analysis engine), experimental programming libraries, cluster computing resources, and data transfer protocols. He/she will interface with senior research staff at multiple institutions and equipment vendors and develop and maintain core components a real-time system for closed-loop brain recording and stimulation, with high data acquisition and computational loads and low-latency requirements. He/she will manage the configuration of the closed-loop brain recording and stimulation system, including system updates and technical support to multiple clinical sites. Finally, he/she will develop and maintain data management systems responsible for transferring experimental data from clinical sites to a centralized server. The ideal candidate will possess exceptional system development skills, be able to effectively communicate new ideas to the management and peer developers, be well versed in modern software development practices including version control, regression testing, software documentation and continuous integration. This is a great opportunity to get exposure to cutting edge research and work in a highly interdisciplinary and intellectually stimulating environment.

The selected applicant will develop and maintain technical computing software (including a real-time neuro-analysis engine), experimental programming libraries, cluster computing resources, and data transfer protocols. He/she will interface with senior research staff at multiple institutions and equipment vendors and develop and maintain core components a real-time system for closed-loop brain recording and stimulation, with high data acquisition and computational loads and low-latency requirements. He/she will manage the configuration of the closed-loop brain recording and stimulation system, including system updates and technical support to multiple clinical sites. Finally, he/she will develop and maintain data management systems responsible for transferring experimental data from clinical sites to a centralized server. The selected candidate will work closely with researchers and data analysts to produce high-impact research publications and will interface with senior staff at multiple institutions and equipment vendors to develop and maintain a high quality, robust software platform for next-generation real-time brain stimulation and recording. He/she will assist in the development of tasks, maintain and further develop pipelines used in data transfer, and develop tools to aid in the processing of experimental results.

Qualifications: Required Qualifications:
-A Bachelor's degree in a technical field such as computer science, engineering, physics, mathematics, etc. with 2-3 years of relevant experience.
-Expertise in Python and Proficiency in C/C++, including development of C/C++ Python extension modules.
-Proficiency with scientific / statistical computing libraries and languages (SciPy, NumPy, pandas, xarray, MATLAB, R, etc.).
-Experience in developing asynchronous/multi-threaded software.
-Experience with real-time computing and collaborative software development, including version control (git, SVN).
-Ability to work proficiently in Windows, Mac, or *nix development environments (including shell-scripting ability and strong familiarity with UNIX terminal).

Preferred qualifications:
-Master's degree or higher.
-Cross-platform software development experience.
-Experience with neural time series analysis.
-Experience developing in Unity.
-Background in machine learning, regression modeling, feature discovery/selection, optimization, exploratory data analysis, data mining, pattern recognition.
-Good communication, inter-personal, and leadership skills.

Reference Number: 02-30503

Salary Grade: C

Employment Type: Exempt

Org: Psychology

Special Requirements: Background check required after a conditional job offer is made. Consideration of the background check will be tailored to the requirements of the job.

Job Family: E-Information Systems/Technology