Jobs

From two to three years of secured funded for working on computational modeling, multi-omics molecular and multi-modal neuroimaging analysis in neurodegeneration (multiple diseases, including AD, PD, and others). Collaborations with many prestigious institutions (e.g. Rush University, Alberta University). Competitive salaries and conditions.

Example of work:

Are you passionate about unraveling the secrets of RNA and deciphering their functional structures? Do you have a strong background in bioinformatics and a burning curiosity to explore the dynamic world of RNA molecules? If so, we invite you to embark on an exciting research journey with us!

🔬 About Us:

At the Computational Biology Research and Analytics (COBRA) Lab at the University of Alberta, we are at the forefront of cutting-edge RNA research. In collaboration with Dr. Lara Mahal (Professor of Chemistry and Canada Excellence Research Chair in Glycomics) we are seeking a highly motivated and talented postdoctoral researcher to join our team of passionate scientists. Our mission is to advance our understanding of RNA biology and its implications in various biological processes.

🧬 Position Overview:

– **Position**: Postdoctoral Researcher in RNA Bioinformatics

– **Location**: Edmonton, Alberta

– **Duration**: One year with possibility of extension

– **Start Date**: As soon as possible

Why Join Us?

– Work in a dynamic and collaborative research environment.

– Access cutting-edge technology and resources for your research.

– Opportunities for career development and networking.

– Competitive salary and benefits package ($70,000 per annum).

Join us in unraveling the mysteries of RNA and making a significant impact in the field of molecular biology. Apply today and become an integral part of our innovative research team!

We seek a postdoctoral fellow to help develop an AI-powered self-driving lab to automate multiscale mapping of multicellular, human biological model systems. This fellowship provides a unique opportunity to work at the intersection of biology, engineering, and artificial intelligence, contributing to the future of precision medicine through innovative approaches. The successful candidate will play a key role in advancing machine learning-driven analysis of high-content imaging data and integrating multi-omics datasets within human organ mimicry systems. This work will involve developing novel computational approaches for biological discovery while engaging in a highly interdisciplinary research environment. 

This is an Acceleration Consortium Post Doctoral Fellowship supervised by Staff Scientists Dr. Ilya Yakavets and Dr. Yimu Zhao in the Human Organ Mimicry self-driving lab (SDL) with a direct reporting line to co-supervisor Professor Gary Bader in the Departments of Computer Science and Molecular Genetics at the University of Toronto. 

The Human Organ Mimicry SDL is an autonomous, AI-driven lab focused on advancing material development, drug discovery, and personalized medicine. By integrating organoids, organ-on-chip technology, biosensors, and machine learning, the lab creates biomimetic models that closely replicate human organ functions and generate clinically relevant data. These models enable medium-throughput, high-content experimentation, accelerating data-driven health research. 

The position provides the chance to contribute to cutting-edge research within a vibrant intellectual community at Canada’s leading university. It offers access to state-of-the-art facilities and an outstanding research environment at the Acceleration Consortium within the University of Toronto, working within a world-class team of scientists dedicated to advancing machine learning applications in human organ mimicry, precision medicine, and more. The Department of Computer Science is globally recognized for its pioneering research in artificial intelligence, while the Department of Molecular Genetics is internationally acclaimed as a premier institution for biomedical and life sciences research and education. Furthermore, the Donnelly Centre for Cellular and Biomolecular Research serves as a hub for interdisciplinary collaboration, fostering the integration of functional genomics, computer science, engineering, and biology to address key challenges in biomedical research (http://www.thedonnellycentre.utoronto.ca). 

Situated within the University of Toronto, one of the most concentrated biomedical research communities globally, this position provides access to extensive resources, including fully affiliated academic hospitals and research institutes. The Greater Toronto Area enhances this exceptional academic environment with its cultural and demographic diversity, as well as one of the highest standards of living in the world.

Salary: Competitive and commensurate with qualifications. 

Application Process:
Interested candidates should submit a CV, brief cover letter, and contact information for three references to gary.bader@utoronto.ca referencing SDL6 in the subject. Applications will be reviewed on a rolling basis. 

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.