Job Watch

Limited Competition: Renewal of Existing NINDS-Supported Clinical Trial Cooperative Agreement Awards (U01 - Clinical Trials Required)

Funding Opportunity PAR-25-149 from the NIH Guide for Grants and Contracts. This limited competition Notice of Funding Opportunity (NOFO) invites renewal applications of existing NINDS-supported clinical trial cooperative agreement awards (U01) requiring additional time and resources to complete the clinical trial.

Oxford Nanopore Technologies: Applied and Regulated Development Scientist

New Scientist - Bioinformatics - Mon, 2024-10-28 05:47
Negotiable: Oxford Nanopore Technologies: We are looking for a highly motivated Applied and Regulated Development scientist with good lab-based skills to join our Applied and Regulated Development team. Oxford, England
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Pilot Projects Investigating Understudied Proteins Associated with Rare Diseases (R03 Clinical Trial Not Allowed)

Funding Opportunity PAR-25-122 from the NIH Guide for Grants and Contracts. The purpose of this notice of funding opportunity (NOFO) is to solicit applications for pilot projects to elucidate a role for understudied proteins in rare disease. Awards will support generation of preliminary data and/or tools around eligible understudied protein(s). A list of eligible proteins is provided and are members of druggable protein families that have a known association with a rare disease. This NOFO is intended to jumpstart research on understudied proteins that are associated with rare diseases and provide applicants with sufficient funding to perform basic biochemical and/or biological work to further the characterization of understudied proteins within the context of rare disease.

King's College London: Research Fellow in the Department of Basic & Clinical Neuroscience

New Scientist - Bioinformatics - Sat, 2024-10-26 20:00
Competitive: King's College London: About us We are part of the King's MND Care and Research Centre, a prize-winning internationally recognized group of clinical and laboratory researc London, United Kingdom
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Pangea Biological: Machine Learning Scientist (Analytical Chemistry - Natural Product Drug Discovery)

New Scientist - Bioinformatics - Fri, 2024-10-25 20:00
Competitive: Pangea Biological: Company Overview: Pangea Bio discovers and develops transformative medicines to treat neurological and neuropsychiatric disorders with large unmet me London, Greater London, United Kingdom
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Altos Labs: Scientist, Computational Biology, Spatial Omics

New Scientist - Bioinformatics - Fri, 2024-10-25 20:00
Competitive: Altos Labs: Our Mission Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can Cambridge, United Kingdom
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Implementation Research for Multi-morbidity Management in the Context of Non-communicable Diseases in Low- and Middle-Income Countries and US Tribal Populations (R61/R33 Clinical Trial Required)

Funding Opportunity PAR-25-223 from the NIH Guide for Grants and Contracts. The National Institutes of Health (NIH) participating Institutes and Centers (ICs), in collaboration with the Global Alliance for Chronic Diseases (GACD), intends to publish Funding Opportunity Announcements (FOAs) to invite applications forimplementation research on noncommunicable diseases (NCDs) in World Bank-defined low- and middle-income countries (LMICs) and American Indian/Alaskan Native (AI/AN) Tribal Nation populations in the United States.

Implementation Research for Multi-morbidity Management in the Context of Non-communicable Diseases in Low- and Middle-Income Countries and US Tribal Populations (R01 Clinical Trial Optional)

Funding Opportunity PAR-25-213 from the NIH Guide for Grants and Contracts. The National Institutes of Health (NIH) participating Institutes and Centers (ICs), in collaboration with the Global Alliance for Chronic Diseases (GACD), intends to publish Funding Opportunity Announcements (FOAs) to invite applications forimplementation research on noncommunicable diseases (NCDs) in World Bank-defined low- and middle-income countries (LMICs) and American Indian/Alaskan Native (AI/AN) Tribal Nation populations in the United States.

Development of Resources and Technologies for Enhancing Rigor, Reproducibility, and Translatability of Animal Models in Biomedical Research (R01 Clinical Trial Not Allowed)

Funding Opportunity PAR-25-076 from the NIH Guide for Grants and Contracts. The Office of Research Infrastructure Programs (ORIP) encourages research project grant applications aimed at developing and implementing broadly applicable technologies, tools, and resources for validating animal models and enhancing rigor, reproducibility, and translatability of animal research. Research projects submitted under this Notice of Funding Opportunity (NOFO) should be hypothesis driven with strong preliminary data. Proposed studies, models, resources, or technologies under this NOFO must either address research interests of multiple NIH Institutes and Centers (ICs), explore multiple organ systems, or be applicable to diseases and processes that impact multiple organ systems in order to align with ORIPs NIH-wide mission and programs. Applications should aim to enhance the rigor, reproducibility, and translatability of animal research through the development and implementation of technologies, tools, and resources that have significant impact across a broad range of research areas using animal models. Applications must demonstrate how the proposed resources and technologies impact rigor and reproducibility of animal studies.

The Metastasis Research Network (MetNet): MetNet Research Projects (U01 Clinical Trial Not Allowed)

Funding Opportunity PAR-25-130 from the NIH Guide for Grants and Contracts. The MetNet is a collection of Research Centers that support using systems level approaches to understand the non-linear, dynamic and emergent processes in metastasis. Considering chronological progression and biological scales, the MetNet seeks to collectively derive a more comprehensive and cohesive picture of metastasis as a whole body, systems-level problem.

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