Job Listings

The English version follows the French. Laboratoire : Le laboratoire de recherche en oncologie pulmonaire intégrative et translationnelle à l’Institut Universitaire de Cardiologie et de Pneumologie de Québec (IUCPQ) – Université Laval (Faculté de Médecine) comprend une équipe multidisciplinaire composée de pathologistes thoraciques et moléculaires, généticiens, biologistes computationnels, bioinformaticiens, professionnels de recherches et étudiants gradués. Il est situé dans un centre de recherche de renommée internationale au sein duquel travaillent en collaboration des chercheurs impliqués en recherche fondamentale, en oncologie, en chirurgie thoracique et en pneumologie. Les membres du laboratoire travaillent en étroite collaboration avec les équipes cliniques de l’IUCPQ, la biobanque institutionnelle et des équipes de l’industrie pharmaceutique et des biotechnologies pour répondre à de grands enjeux ciblés sur les besoins des patients. Les projets du laboratoire intègrent l’analyses de multiples jeux de données -omiques, comme la transcriptomique et la protéomique spatiale, afin de répondre à des questions cliniques centrées sur les besoins des patients. Poste : Nous cherchons un étudiant(e) à la maîtrise pour intégrer notre équipe de recherche à l’automne 2025 ou l’hiver 2026. L’étudiant(e) sera encouragé(e) à faire un stage rémunéré de 3 mois débutant à l’été 2025 avant le début de sa maîtrise. L’étudiant(e) travaillera sous la supervision des Dr. Fabien Lamaze (biologiste computationnel, chercheur associé), Dr. Sébastien Renault (bioinformaticien) et Dre. Andréanne Gagné (pathologiste et chercheur). Description du projet : L’étudiant(e) sera impliqué(e) dans un projet de recherche translationnel sur un sous-type de cancer du poumon très agressif pour lequel il y a peu d’options thérapeutiques, soit les carcinomes à petites cellules du poumon (SCLC). Récemment, des analyses transcriptomiques ont permis de classer les SCLC en quatre sous-groupes qui ont une valeur potentiellement pronostique et thérapeutique. L’objectif est de corréler ces sous-groupes avec le pronostic des patients et d’identifier leurs mécanismes de régulation. Ceci permettra de mieux comprendre la biologie de ces tumeurs afin de mieux prédire le comportement clinique des tumeurs, trouver des mécanismes potentiels à des thérapies existantes et/ou découvrir de nouvelles avenues thérapeutiques. Via la biobanque institutionnelle, l’équipe a accès à une large cohorte unique et bien caractérisée. Ceci permettra à l’étudiant(e) sélectionné(e) de travailler sur l’analyse des données en utilisant des outils de bioinformatique, d’apprentissage machine, de transcriptique, de transcriptomique spatiale et de pathomique. ___ Lab: The Integrative and Translational Lung Oncology Research Laboratory at the Institut Universitaire de Cardiologie et de Pneumologie de Québec (IUCPQ) – Université Laval (Faculty of Medicine) is a multidisciplinary team composed of thoracic and molecular pathologists, geneticists, computational biologists, bioinformaticians, research professionals, and graduate students. The lab is located within a world-renowned research center where researchers in basic science, oncology, thoracic surgery, and pulmonology collaborate closely. The lab works in tight collaboration with IUCPQ’s clinical teams, the institutional biobank, as well as pharmaceutical and biotechnology industry partners to address major challenges focused on patient needs. Projects integrate the analysis of multiple -omics datasets, such as transcriptomic and spatial proteomic mapping, to answer clinically driven, patient-centered questions. Position: We are seeking a Master’s student to join our research team starting in Fall 2025 or Winter 2026. The student will be encouraged to complete a paid 3-month internship beginning in Summer 2025 prior to starting their Master’s. The student will work under the supervision of Dr. Fabien Lamaze (Computational Biologist, Associate Researcher), Dr. Sébastien Renault (Bioinformatician), and Dr. Andréanne Gagné (Pathologist and Researcher). Project Description: The student will be involved in a translational research project focused on a highly aggressive subtype of lung cancer with limited therapeutic options: small cell lung carcinoma (SCLC). Recent transcriptomic analyses have classified SCLC into four molecular subtypes with potential prognostic and therapeutic relevance. The project’s objective is to correlate these subtypes with patient outcomes and identify their regulatory mechanisms. This work aims to improve our understanding of SCLC biology to better predict clinical behavior, uncover mechanisms exploitable by existing therapies, and potentially discover new therapeutic avenues.Through the institutional biobank, the team has access to a large, unique, and well-characterized cohort. The selected student will work on data analysis using bioinformatics, machine learning, transcriptomics, spatial transcriptomics, and pathomics tools.

Laboratoire : Laboratoire de Bioinformatique et Protéomique (ADLab) – Pr. Arnaud Droit. Le laboratoire est spécialisé dans le développement de méthodes computationnelles avancées et d’approches statistiques pour l’analyse de données massives. ADLab collabore avec des partenaires académiques et industriels à l’échelle internationale et dispose d’infrastructures de calcul de haut niveau. Institution : Faculté de Médecine, Université Laval, Québec, Canada Description du poste : Le laboratoire du Pr. Arnaud Droit (ADLab) recrute un(e) doctorant(e) en informatique pour développer et appliquer des algorithmes quantiques, destinés à l’analyse de données biologiques. Le projet s’articulera autour de la conception de solutions algorithmiques innovantes, appliquées à des problématiques de bioinformatique. Le ou la candidat(e) intégrera un environnement de recherche dynamique avec accès à des infrastructures de calcul avancées et des collaborations internationales.

Laboratoire : Laboratoire de Bioinformatique et Protéomique (ADLab) – Pr. Arnaud Droit. Le laboratoire est spécialisé dans le développement de méthodes computationnelles avancées et d’approches d’intelligence artificielle et statistiques pour l’analyse de données massives. ADLab collabore avec des partenaires académiques et industriels à l’échelle internationale et dispose d’infrastructures de calcul de haut niveau. Institution : Faculté de Médecine, Université Laval, Québec, Canada Description du poste : Le laboratoire du Pr. Arnaud Droit (ADLab) recrute un(e) étudiant(e) en bioinformatique pour travailler sur l’analyse de données de protéomique issues de spectromètres de masse de dernière génération. Cette recherche s’effectuera dans le cadre de la lutte contre l’antibiorésistance, qui représente une menace majeure pour la santé publique. Cette problématique est la conséquence de la surutilisation des antibiotiques qui favorise l’émergence de bactéries résistantes, rendant de nombreuses infections difficiles à soigner. Il est ainsi crucial de développer de nouvelles approches pour détecter et contrer ces résistances. Le ou la candidat(e) contribuera ainsi au développement d’outils informatiques pour l’analyse et la validation de données protéomiques ainsi qu’à l’application de méthodes d’apprentissage automatique pour l’identification de biomarqueurs diagnostiques dans des fluides biologiques (détection de bactéries, résistance aux traitements, etc.).

Whole Person Benefit Packages | Relocation Assistance |Research Faculty Incentive Plans Moffitt Cancer Center, the top-ranked NCI-designated comprehensive cancer center in the Southeastern United States, is seeking a faculty member in the tenure-earning rank of Associate/Senior Member (Associate/Full Professor equivalent) to be the Vice-Chair for the Department of Biostatistics and Bioinformatics and the Associate Scientific Director for the Biostatistics and Bioinformatics Shared Resource (BBSR). Position Highlights: The growing Department of Biostatistics and Bioinformatics and corresponding Shared Resource currently has 17 faculty and approximately 26 BBSR staff members engaged in a wide range of statistical and bioinformatics research and collaborations on clinical, translational, population and biological studies in cancer prevention, early detection, treatment, prognosis and survivorship, drawing on expertise in novel therapeutic and drug discovery, prognostic and predictive biomarker development, chemoprevention, microbiome, high throughput genomics, proteomics & metabolomics, next-generation sequencing, spatial biology, molecular epidemiology, behavioral interventions, comparative effectiveness research, clinical trial design, and precision medicine. Many of these projects draw upon Moffitt’s Total Cancer Care initiative, which provides access to a comprehensive set of clinical and molecular data on a large number of cancer patients. The Department of Biostatistics and Bioinformatics is the largest academic department at Moffitt and one of three departments in the academic Division of Quantitative Sciences within the Moffitt Research Institute. Alongside the Departments of Machine Learning and Integrated Mathematical Oncology, the Department of Biostatistics and Bioinformatics offers a unique environment for quantitative scientists focused exclusively on cancer. Institutional investments in the Moffitt Cancer Analytics Platform, high performance computing, and the Total Cancer Care Protocol offer unique resources for data-driven team science. Tampa is a thriving metropolitan city that provides its residents a high quality of life. The Tampa Bay area has become a hub for ground-breaking research, welcoming individuals from around the globe. This diverse city is engulfed with rich culture, year-round activities for all, beautiful beaches, amazing cuisine and so much more. Questions about the opportunity may be directed to the Department Chair, Dr. Xuefeng Wang at xuefeng.wang@moffitt.org or search committee chair, Dr. Michael Schell at Michael.Schell@moffitt.org. Review of applications will begin immediately. Please be sure to attach your CV and cover letter. To apply, visit our website MOFFITT.org/Careers and refer to requisition number 83761

Whole Person Benefit Packages | Relocation Assistance |Research Faculty Incentive Plans The growing Department of Biostatistics and Bioinformatics and corresponding Shared Resource currently has 17 faculty and approximately 26 BBSR staff members engaged in a wide range of statistical and bioinformatics research and collaborations on clinical, translational, population and biological studies in cancer prevention, early detection, treatment, prognosis and survivorship, drawing on expertise in novel therapeutic and drug discovery, prognostic and predictive biomarker development, chemoprevention, microbiome, high throughput genomics, proteomics & metabolomics, next-generation sequencing, spatial biology, molecular epidemiology, behavioral interventions, comparative effectiveness research, clinical trial design, and precision medicine. Many of these projects draw upon Moffitt’s Total Cancer Care initiative, which provides access to a comprehensive set of clinical and molecular data on a large number of cancer patients. The Department of Biostatistics and Bioinformatics is the largest academic department at Moffitt and one of three departments in the academic Division of Quantitative Sciences within the Moffitt Research Institute. Alongside the Departments of Machine Learning and Integrated Mathematical Oncology, the Department of Biostatistics and Bioinformatics offers a unique environment for quantitative scientists focused exclusively on cancer. Institutional investments in the Moffitt Cancer Analytics Platform, high-performance computing, and the Total Cancer Care Protocol offer unique resources for data-driven team science. Interested applicants should send a single PDF file that includes a cover letter summarizing their research training and accomplishments, a personal statement of scientific interests and goals, current CV with recent publications, and contact information for three references to Dr. Xiaoqing Yu, Search Committee Chair, at Xiaoqing.Yu@moffitt.org. Review of applications will begin immediately and continue until the position is filled. Tampa is a thriving metropolitan city that provides its residents a high quality of life. The Tampa Bay area has become a hub for ground-breaking research, welcoming individuals from around the globe. This diverse city is engulfed with rich culture, year-round activities for all, beautiful beaches, amazing cuisine and so much more. Equal Employment Opportunity Moffitt is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, or protected veteran or disabled status. Moffitt seeks candidates whose skills, and personal and professional experience, have prepared them to contribute to our commitment to diversity and excellence.

Subject area description Miscarriage is the most common pregnancy complication, with over 23 million pregnancies ending in miscarriage every year.  This project aims to identify fetal genetic factors (SNP and de novo copy number variants) behind miscarriage, particularly among fetuses with normal chromosome counts. The postdoc fellow will lead a project using large-scale genotyping array data from miscarried fetuses and their mothers (including calling of aneuploidies and copy number variants) and contribute to ongoing efforts in this field (GWAS, meta-analyses, etc).

Job Summary The Centre for Molecular Medicine and Therapeutics at the University of British Columbia seeks applications for a Research Associate in the Wasserman Lab working on the Silent Genomes Project.  The Wasserman laboratory partners with a strong genetics community to develop and apply computational (bioinformatics) methods to improve diagnosis for individuals with rare genetic disorders caused by variations in genome sequences.  The Silent Genomes Project is a national collaboration focused on the establishment of an Indigenous Background Variant Library under Indigenous governance and oversight.   Based on the campus of BC Children’s Hospital, the Wasserman laboratory is the lead laboratory for the technical implementation of the Indigenous Background Variant Library, including the implementation of software pipelines for processing whole genome sequence data generated at an approved genome centre, the implementation of quality control analyses, the construction of the database to host the generated genetic data and the implementation of the interface via which the data can be accessed by approved users.  The work, while computational in focus, requires close interaction with an Indigenous governance committee, collaborators and trainees.  The ideal candidate will apply computational skills to develop computationally efficient and reproducible results for the detection of genetic variants across whole genome sequences from hundreds to thousands of individual samples, establish and document standard operating procedures for such analyses, incorporate new innovative methods for detection of genetic variants (either for new classes of variants or using data from different sequencing techniques (e.g. long-read)), and contribute to the development of scientific manuscripts, reports and funding applications.  Central to the work, is extraordinary attention to the sensitivity of the data being processed, with particular emphasis on the rights of Indigenous peoples and the central importance of adhering to the Indigenous governance procedures within the project. Experience with whole genome sequence processing and analysis, pipeline management software (e.g. Nextflow or SnakeMake) and working with highly sensitive genetic data are strong advantages.   Organizational Status This is a leadership role, requiring a high degree of independence, initiative and professional judgement.  The successful candidate reports to and receives guidance from Dr. W. Wasserman (Professor, Medical Genetics, Project Leader), with input and advice from Dr. L. Arbour (Medical Geneticist, Co-Project Leader) and Dr. Nadine Caron (Co-Project Leader) as needed.  The successful candidate supervises staff members and possibly University students or volunteers working on Silent Genomes.     Consequence of Error/Judgement Lack of careful attention to protocols and regulatory and ethical guidelines could suspend the Investigator’s laboratory and/or the University as a site for further research and/or funding. Performance must strictly conform to research protocols, Tri-Council policy statement, and standard Canadian guidelines for health research involving Indigenous People.   A high level of cultural competency and sensitivity is necessary in this position, as any insensitive actions could jeopardize our longstanding research relationship with the Indigenous communities we work with.   Errors in the dissemination of DNA sequence data or any breach of confidentiality could jeopardize this research study and Dr. Wasserman’s research program. A confidentiality agreement must be signed, stating that any identifying and/or personal information will be held in the strictest confidence.  Inaccuracies or incompleteness of data collection, or errors in the collection and handling of biological samples could result in erroneous data analysis and study results; therefore, it is imperative that the successful candidate is detail- oriented and very careful with their work.   Supervision Received The incumbent works with wide latitude and demonstrates a high degree of independence.  They report to and receive guidance from Dr. W. Wasserman (Professor, Medical Genetics, Project Leader).   Supervision Given The incumbent provides direction and expertise to project team members, including research assistants, overseeing the daily activities of trainees, and directing a scientific computer programmer participating on the Silent Genomes project.

The Centre for Molecular Medicine and Therapeutics at the University of British Columbia seeks applications for a Post-Doctoral Scientist in the Wasserman Lab working on the Silent Genomes Project.  The Wasserman laboratory partners with a strong genetics community to develop and apply computational (bioinformatics) methods to improve diagnosis for individuals with rare genetic disorders caused by variations in genome sequences. The Silent Genomes Project is a national collaboration focused on the establishment of an Indigenous Background Variant Library under Indigenous governance and oversight.   Based on the campus of BC Children’s Hospital, the Wasserman laboratory is the lead laboratory for the technical implementation of the Indigenous Background Variant Library, including the implementation of software pipelines for processing whole genome sequence data generated at an approved genome centre, the implementation of quality control analyses, the construction of the database to host the generated genetic data and the implementation of the interface via which the data can be accessed by approved users.  The work, while computational in focus, requires close interaction with an Indigenous governance committee, collaborators and trainees.  In addition to engineering, the Wasserman laboratory seeks to develop innovative bioinformatics methods for assessing the quality of and improving the library.  The candidate will apply computational skills to develop computationally efficient and reproducible results for the detection of genetic variants across whole genome sequences, create methods to separate shared from not shared genetic variation data from related individuals, create methods to predict the number of novel genetic variants (compared to an existing background variation database), and develop procedures for assessing the presence of structural variants, initially detected in long-read sequencing data, in short-read whole genome sequence data, and contribute to the development of scientific manuscripts, reports and funding applications.  Central to the work, is extraordinary attention to the sensitivity of the data being processed, with particular emphasis on the rights of Indigenous peoples and the central importance of adhering to the Indigenous governance procedures within the project. Experience with whole genome sequence processing and analysis, pipeline management software (e.g. Nextflow) and working with highly sensitive genetic data are strong advantages.   Organizational Status This is a leadership role, requiring a high degree of independence, initiative and professional judgement.  The successful candidate reports to and receives guidance from Dr. W. Wasserman (Professor, Medical Genetics, Project Leader).  The successful candidate supervises staff members and possibly University students or volunteers working on Silent Genomes.  They will contribute to development of reports for oversight bodies and funding organizations.   Supervision Received The incumbent works with wide latitude and demonstrates a high degree of independence.  They report to and receive guidance from Dr. W. Wasserman (Professor, Medical Genetics, Project Leader)   Supervision Given The incumbent provides expertise to project team members, including  University students and other trainees participating on the Silent Genomes project.   Consequence of Error/Judgement Lack of careful attention to protocols and regulatory and ethical guidelines could suspend the Investigator and/or University as a site for further research and/or funding. Performance must strictly conform to research protocols, Tri-Council policy statement, and standard Canadian guidelines for health research involving Indigenous People. A high level of cultural competency and sensitivity is necessary in this position, as any insensitive actions could jeopardize our longstanding research relationship with the Indigenous communities we work with. Errors in the dissemination of DNA sequence data or any breach of confidentiality could jeopardize this research study and Dr. Wasserman’s research program. A confidentiality agreement must be signed, stating that any identifying and/or personal information will be held in the strictest confidence.

University College Dublin is recruiting fifty early-career faculty through the Ad Astra Fellowship programme. Within the School of Medicine there are two posts within the broad area of AI in medicine. The application of artificial intelligence in clinical medicine and biomedical research and practice is a key strategic priority of the School. In this post, the successful applicant will be involved in state-of-the-art research and teaching in the application of AI to medicine and medical research. This will cover areas including, but not limited to the role of AI in diagnostics, data analysis and clinical intervention decisions.

The PI will be expected to mentor trainees and early career investigators, to build collaborations both within and outside the OICR community, and to work with FACIT, OICR’s commercialization partner, to translate research findings into real-world products and services. In addition to base funds provided by the Institute to support the PI’s salary and core personnel, the PI is expected to raise additional research funds from external competitive granting agencies. OICR will assist the PI in obtaining a faculty appointment at the University of Toronto or another affiliated academic institution.   In the case of a successful senior candidate, OICR will provide opportunities to take on leadership responsibilities within the Computational Biology program. The incumbent will work with other senior leaders at OICR and make significant contributions to develop strategic research priorities and operational tactics.   Housed within OICR’s Adaptive Oncology theme, the Computational Biology Program provides a robust intellectual environment with multiple investigators working with technologies ranging from spatial ‘omics to large language models of clinical records. An institutional cluster comprising ~9,000 CPU threads, and 18 GPU servers with a total of 36 NVIDIA CUDA cards as well as a large OpenStack virtualization environment, is available to support analysis by members of the Program. In addition, extensive compute resources, including large GPU clusters, are available to OICR faculty via Canada’s Digital Research Alliance.   OICR is a multi-disciplinary, team-science-driven translational research institute with PIs working in the areas of medical imaging instrumentation, robotics, drug design and development, biomarker discovery and assay development, spatial biology, and genomics. In addition to the facilities provided by the Computational Biology Program, the candidate will have access to a series of technology platforms for large-scale molecular data generation ranging from whole genome sequencing of challenging clinical specimens, to spatial transcriptomics and proteomics, cell-free DNA analysis, long-read sequencing, and digital histopathology. OICR develops and hosts multiple biobanks comprising hundreds of thousands of tissue and blood specimens, including the Ontario Health Study and the Ontario Tumour Bank. In addition, OICR develops and operates multiple data-rich biological databases including the international ICGC-ARGO Cancer Genome data platform, the Ontario Hereditary Cancer Research Network, and the Ontario node of the TFRI Marathon of Hope Comprehensive Cancer Centre Network. We are the host institution for the Global Alliance for Genomics in Health and a co-developer of the Pan-Canadian Genome Library. Finally, we believe in open-source and community development and are a signatory to the San Francisco Declaration on Research Assessment (DORA).   Please visit https://oicr.on.ca/research-portfolio/ for details on our research portfolio.