Hamed Gilzad Kohan
5 days ago
PhD Student in Computational Pharmacology, Quantitative Systems Pharmacology, and Machine Learning Massachusetts College of Pharmacy and Health Sciences in United States
Degree Level
PhD
Field of study
Physiology
Funding
PhD student opening in the lab; funding details are not specified in the post. The program begins in September 2027 and applications go through the MCPHS admissions process.
Country
United States
University
Massachusetts College of Pharmacy and Health Sciences

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About this position
Hamed Gilzad Kohan, Associate Professor at Massachusetts College of Pharmacy and Health Sciences (MCPHS), is recruiting PhD student(s) for a computational pharmacology project in Boston, United States.
The position focuses on quantitative systems pharmacology (QSP), model-informed drug development (MIDD), hybrid mechanistic and machine learning methods, and an unsolved clinical prediction problem with experimental validation from collaborating labs.
Ideal applicants should be comfortable with Python, Julia, or R, have some exposure to Bayesian inference, and come from pharmaceutical sciences, engineering, applied mathematics, and/or computational biology. A strong curiosity about physiology is highlighted as especially important.
This is a PhD opening starting in September 2027. The post does not specify funding details, but it states that applications go through the MCPHS admissions process.
How to apply: use the MCPHS application portal link provided in the post. For questions about the project or fit, email [email protected] with a short note describing a modeling or computational project you have worked on.
Funding details
PhD student opening in the lab; funding details are not specified in the post. The program begins in September 2027 and applications go through the MCPHS admissions process.
What's required
Applicants should have fluency in Python, Julia, or R, some exposure to Bayesian inference, and a background in pharmaceutical sciences, engineering, applied math, and/or computational biology. Strong curiosity about physiology is emphasized, and applicants who are unsure are encouraged to apply.
How to apply
Apply through the MCPHS admissions process using the provided portal link. If you have questions about the project or fit, email [email protected] with a short note about a modeling or computational project you have worked on.
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