Long Island University (LIU) hosts a leading Dassault Systèmes Center of Excellence (CoE) in Life Sciences. Through our collaboration with Dassault Systèmes, we are spearheading the digital transformation of life science, education and clinical practice by leveraging advanced computational methods, AI and in-silico modeling.
We are seeking highly qualified Ph.D. students to work under the supervision of Dr. Nicolas Gallo (School of Engineering) and Dr. Kenza Benzeroual (College of Pharmacy) to contribute to the research on the virtual twin modeling of the heart (i.e., cardiotoxicity). In this role, you will work closely with your research advisors to conduct Ph.D. research in alignment with the CoE research initiatives.
o Enrollment in a Ph.D. program with strong understanding of the literature in pharmacogenetics.
o Strong technical expertise in Molecular Dynamics simulation (Discovery Studio)
o Demonstrated working knowledge in one or more programming languages: Python, MATLAB or C++.
o Ability to document and present analytical results.
o Ability to conduct independent research and work collaboratively with the research advisors.
To Apply
Interested candidates should submit a cover letter, CV, and a list of three references to Dr. Nicolas Gallo at nicolas.gallo@liu.edu . Applications must also be submitted online at (https://jobs.liu.edu/#/list).
Long Island University (LIU) has formed a research and innovation partnership with Dassault Systèmes in life sciences. The collaboration focuses on impactful research in pharmaceutical sciences, precision medicine, and healthcare in the digital age. The research involves the development of "Virtual Twins," digital models of human anatomy, to advance precision medicine.
LIU has also opened in 2020 a state-of-the-art simulation and high-performance computing laboratory equipped with Dassault Systèmes' 3D, augmented reality, and virtual reality software. This facility supports experiential research, education, and training in various fields, including AI, robotics, cybersecurity, data analytics, and drug discovery.
LIU is committed to extending equal opportunity in employment to all qualified candidates who can contribute to the diversity and excellence of our academic community. LIU encourages applications from all qualified individuals without regard to race, color, religion, genetic information, sexual orientation, gender and/or gender identity or expression, marital or parental status, national origin, ethnicity, citizenship status, veteran or military status, age, disability or any other basis protected by applicable local, state or federal laws. Hiring is contingent on eligibility to work in the United States.