RSS Feed Source: Academic Keys

JOB TITLE
Postdoctoral Fellow in Computational Clinical Cardiac Electrophysiology

LOCATION
Worcester

DEPARTMENT NAME
Biomedical Engineering Department – NFR JM

DIVISION NAME
Worcester Polytechnic Institute – WPI

JOB DESCRIPTION SUMMARY

JOB DESCRIPTION

Core Duties:

Collaborate closely with the principal investigator to design and implement research studies. Examine experimental and clinical data, maintaining meticulous laboratory records. Consistently share findings with the principal investigator and fellow researchers. Aid in crafting technical reports, drafting grant proposals, and preparing scientific presentations. Play a pivotal role in peer-reviewed publications, as both a lead and co-author. Provide mentorship to both undergraduate and graduate students. Collaborate with a diverse team of research specialists.

Preferred Qualifications:

A Ph.D. in electrical engineering, computer science & engineering, applied statistics/mathematics, or a closely related field; familiarity with cardiac electrophysiology modeling is advantages. A solid background and interest in numeric optimization, statistical inference, and machine learning and deep learning techniques.

Click this link to continue reading the article on the source website.

RSS Feed Source: Academic Keys

With multiple grants and research infrastructure provided by the U.S. National Science Foundation, researchers have shown that a newly developed material, niobium phosphide, can conduct electricity better than copper in films that are only a few atoms thick. These films can also be created and deposited at sufficiently low temperatures for compatibility with modern computer chip fabrication — and may help make future electronics more powerful and energy efficient.

So far, the best conductor candidates to outperform copper in nanoelectronics have had only exact crystalline structures, meaning they require very high temperatures to be formed. These new niobium phosphide films are the first examples of noncrystalline materials that become better conductors as they get thinner. The research is led by Standford University and results were published in Science.

“We are breaking a fundamental bottleneck of traditional materials like copper,” says Asir Intisar Khan, a postdoctoral researcher at Stanford University and an author on the research paper. “Our niobium phosphide conductors show that it’s possible to send faster, more efficient signals through ultrathin wires. This could improve the energy efficiency of future chips, and even small gains add up when many chips are used, such as in the massive data centers that store and process information today.”

RSS Feed Source: Academic Keys

Implementation Update: Promoting Maximal Transparency Under the NIH Guidelines for Research Involving Recombinant or Synthetic Nucleic Acid Molecules

Institutional Biosafety Committees (IBCs) serve as a critical linchpin in ensuring the safe and responsible conduct of research. Since the issuance of the NIH Guidelines for Research Involving Recombinant or Synthetic Nucleic Acid Molecules (NIH Guidelines) in 1976, IBCs have expanded in number to the thousands and have voluntarily expanded their roles to encompass new research approaches as they arise.

IBCs continue to serve as a pillar of biosafety oversight and are essential in building trust on behalf of the biomedical research enterprise. Under the NIH Guidelines, this expectation is a mandate and as such, NIH is reinforcing its commitment to working with IBCs to ensure transparency in biosafety oversight by updating its implementation expectations to protect the safety of all

Click this link to continue reading the article on the source website.

RSS Feed Source: Academic Keys

Protecting Human Genomic Data when Developing Generative Artificial Intelligence Tools and Applications

Artificial intelligence (AI) tools and applications are proving to be transformative for driving new biomedical research advances. While development and use of generative AI is becoming increasingly prevalent, NIH urges the research community to remain vigilant of potential risks of inadvertent data disclosure when sharing AI tools and applications. Specifically, NIH reminds researchers that:

The Genomic Data Sharing (GDS) Policy and the subsequent Data Use Certification (DUC) Agreement prohibit users from distributing controlled-access data (including genomic or associated data) or their Data Derivatives to any entity or individual not identified in their Data Access Request without appropriate written approvals from the NIH. Sharing, retaining, or training generative AI models using controlled-access human genomic data may risk disclosing controlled-access data and, thus, violates the Non-Transferability provision of

Click this link to continue reading the article on the source website.