Overview
Brown University is offering a postdoctoral associate position focused on machine learning and biomolecular simulation. This two-year role is funded by the NIH and aims to address the opioid epidemic by identifying new drug candidates through a collaborative approach involving multiple departments, including Chemistry, Computer Science, Engineering, and Pharmacology. This opportunity is significant for the AI/ML community as it combines advanced computational techniques with pressing health challenges.
Background & Relevance
The intersection of machine learning and biomolecular simulation is a rapidly evolving field that holds great promise for drug discovery and development. By leveraging computational methods, researchers can simulate molecular interactions and predict the efficacy of potential drug candidates. This research area is crucial, particularly in the context of public health issues like the opioid crisis, where innovative solutions are urgently needed. The collaborative nature of this project enhances its relevance, as it brings together expertise from various scientific disciplines.
Key Details
- Position Type: Postdoctoral Associate
- Duration: Two years
- Funding: NIH-funded
- Location: Brown University, Providence, RI
- Start Date: Expected winter 2019
- Application Email: brenda_rubenstein@brown.edu
Eligibility & Participation
This position is targeted at individuals with a strong background in machine learning and/or biomolecular simulation. Ideal candidates should possess programming skills in C, C++, and Python, along with experience in related machine learning libraries. The role is designed for those who can work collaboratively and demonstrate creativity and independent thought.
Submission or Application Guidelines
Interested candidates should submit the following materials via email to Brenda Rubenstein:
– A CV
– A brief personal statement outlining their interest in the position
– Two or more professional recommendations
Top candidates will be interviewed shortly after application submission. It is important that applicants have completed their Ph.D. prior to the expected start date.
Additional Context / Real-World Relevance
The research conducted in this position will contribute to the broader field of drug discovery, utilizing machine learning to enhance the understanding of biomolecular interactions. This approach not only aids in the identification of new therapeutic candidates but also exemplifies the growing importance of interdisciplinary collaboration in tackling complex health issues. The skills developed in this role will be valuable for future endeavors in both academia and industry.
Conclusion
This postdoctoral position at Brown University presents an exciting opportunity for researchers interested in the application of machine learning to real-world problems. Those who meet the qualifications are encouraged to apply and contribute to impactful research aimed at addressing critical health challenges. Explore this opportunity and consider how your expertise can make a difference in the field.
Category: PhD & Postdoc Positions
Tags: machine learning, biomolecular simulation, drug discovery, Brown University, computational biology, interdisciplinary research, C++, Python, molecular dynamics, Monte Carlo methods
