Jobs

The Harvard Medical School Curriculum Fellows Program (HMS CFP) is seeking applications for a Biomedical Informatics Curriculum Fellow (CF) for the Department of Biomedical Informatics. This postdoctoral program targets early-career scientist-educators, emphasizing curriculum development, teaching, and educational programming in the biological and biomedical sciences.

The Biomedical Informatics Curriculum Fellow collaborates with a diverse cohort of Curriculum Fellows, leveraging individual expertise while closely engaging with Harvard Medical School faculty and administration to craft, implement, and assess evidence-based graduate training. Fellows benefit from mentorship and career guidance, nurturing their growth as educators and facilitating success across various education-focused careers. Further details are available on our website (https://curriculumfellows.hms.harvard.edu/).

The primary role of the Biomedical Informatics Curriculum Fellow will be to support the Master of Medical Sciences in Biomedical Informatics (MMSc-BMI) program housed in the Department of Biomedical Informatics at Harvard Medical School. This program includes a rigorous combination of core coursework and a year-long full-time thesis research project. As part of the team leading this master’s program, the curriculum fellow will ensure that the program’s offerings provide opportunities for students to develop skills in data science in the context of medicine and biological science to improve human health.

The CF will report directly to and receive mentorship from Dr. Aparna Nathan (Associate Director of the MMSc-BMI program) and Dr. Aimee Hollander (the Curriculum Fellows Program Director). The MMSc-BMI program will work with the successful candidate to identify a faculty mentor in their scientific area of expertise.

Start Date:

The ideal start date for this Curriculum Fellow is approximately April 28, 2025, however there is flexibility to start later. This is a full-time position and the candidate will be expected to work in person on the HMS campus in Boston, MA 3-4 days per week. The CF appointment is renewable annually for a maximum of three years and is non-tenure-track.

Application Deadline & Instructions:

Applications received by February 1st, 2025 will receive a full review. Applicants who apply after the deadline must email cfp@hms.harvard.edu to alert the hiring team you’ve applied.

To apply, CLICK HERE, or copy the application URL into your browser: https://academicpositions.harvard.edu/postings/14481 

Below are the required application materials needed to apply:

• A cover letter that addresses your interest in and qualifications for the position. Please highlight your experience in teaching, curriculum development and biomedical informatics research in your cover letter.
• A curriculum vitae.
• A teaching statement. The teaching statement is an opportunity to describe your philosophy of teaching in the context of your own experiences. A discussion of diversity, equity and inclusion is an important component of the teaching statement. Submissions will be evaluated according to the guidelines found on our website, here, https://curriculumfellows.hms.harvard.edu/teaching-statement-guidelines
• The names and contact information of three professional references.

If you have any questions specific to the program or fellowship, please email: cfp@hms.harvard.edu

Microbial biomarkers to improve the efficacy of GDNF treatment for Hirschsprung disease

Context

Hirschsprung disease is a deadly congenital malformation where the enteric nervous system (ENS) is missing from the colon. Recently, we found that a GDNF-based treatment can induce the formation of a new ENS in the colon of mouse models of Hirschsprung disease, and significantly improve gastrointestinal functions and survival of these mice. However, we have observed variability in the response to GDNF treatment among individuals, with some mice failing to respond while others respond positively. In collaboration with our project partner Neurenati, we are carrying out studies to understand why, and thereby improve the efficacy of the treatment.

Project Title: The H5Nx Genomic Landscape: Predictive Modelling of Host and Antigenic Transitions

A funded Postdoctoral Fellow opportunity is available in under the co-supervision of Dr. Zvonimir Poljak (University of Guelph) and Dr. Finlay Maguire (Dalhousie University).

This is a full-time one-year position, with the possibility of extension, at the University of Guelph. This position is supported by the Canadian Institute of Health Research/Public Health Agency of Canada’s Avian Influenza One Health Research Funding Opportunity with contributions from NSERC.

Date: September 23, 2024

Postdoc/PhD positions in saRNA for Vaccine Development

We are seeking applications for multiple Senior Researcher positions, available immediately for exceptionally motivated Postdoctoral Fellows or PhD students. These positions offer a unique opportunity to contribute to a pioneering project applying artificial intelligence and machine learning to the development of RNA vaccines against emerging viral threats such as Influenza, Lassa, and Orthopox viruses.

Project Overview: This ambitious project utilises self-amplifying RNA (saRNA) technology, which offers the potential for more potent immune responses at lower doses compared to traditional mRNA vaccines. Our approach focuses on the use of structural RNA bioinformatics to design vaccine candidates and predict the effects of viral mutations, enhancing our ability to respond rapidly to evolving pandemic threats.

A post-doctoral fellowships (PDF) position in the field of machine learning/computational biology is available in the School of Biomedical Engineering and Department of Pathology and Laboratory Medicine at the University of British Columbia/Vancouver General Hospital. The incumbents will join an interdisciplinary team working to establish a program on machine learning applications in pathology and genomics. Candidates are expected to have extensive experience in one or more of the following areas: diverse areas of machine learning and statistics especially deep neural networks, statistics, and image processing.

The candidate will play an important role in the project team, including authoring grants, conducting large-scale international projects, managing collaborations, disseminating research findings, and assisting in managing junior lab members.

The successful candidate will report to the Principal Investigator (Director of AI Research at OVCARE, Dr. Ali Bashashati).