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Field
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. Strong experience with Python and at least one deep learning framework such as PyTorch, PyTorch Lightning, TensorFlow or JAX. Familiarity with packages and technologies such as NumPy, Pandas, Scikit-learn
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. Strong experience with Python and at least one deep learning framework such as PyTorch, PyTorch Lightning, TensorFlow or JAX. Familiarity with packages and technologies such as NumPy, Pandas, Scikit-learn
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(Python, JavaScript), deep neural networks and computer vision; Design and implementation of database systems; Design and implementation of application programming interfaces, server-based and cloud
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for strong data management, documentation, and other tools that support replicable research practices High proficiency in at least one language or statistical package (e.g., Stata, R, Python) Demonstrated
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resulting from this researc.h Who You Are: Ph.D. in Computational Biology, Bioinformatics, Human Genetics, Biostatistics, Computer Science or related field. Demonstrated proficiency with R or Python
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research methods (e.g., interactive Qualtrics surveys; longitudinal surveys; ESM; surveys with integrated third-party services); Familiarity with programming (e.g., Python, C++, Java); Familiarity with agent
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(e.g., MATLAB, bash, python, etc.) are required. Applicants who have recently completed their terminal degree and plan to develop an independent research career are especially encouraged to apply
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, Python, and/or C++) A strong track record of research output, including journal publications and conference contributions Expertise or strong interest in one or more of the following areas: Computational
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. Possess relevant hands-on experience in Python, Java, C++ etc. and corresponding development environments.
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. ● Computational skills is a plus (e.g., experience with computational modeling, AI models, familiarity with Python, etc) ● Familiarity with EEG, Brain-Computer Interfaces, biofeedback systems, or biomarkers