Clinical Research Scientist - Oncology
About Qure.AI:
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<\/span><\/span><\/b>Qure.ai is the world's fastest\-growing medical AI company, boasting an impressive 13 FDA and 62 CE marking clearances to date. We develop cutting\-edge solutions that significantly enhance patient outcomes across various care domains, including lung cancer, tuberculosis, and stroke. Our innovative technologies have positively impacted over 22 million patients in more than 90 countries worldwide. At Qure.ai, we are committed to fostering a diverse and inclusive workplace and are proud to be an equal\-opportunity employer.
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<\/span><\/span><\/span>About the job
<\/span><\/span>Job Title:<\/span><\/span><\/b> <\/span><\/span><\/span>Clinical Research Scientist \u2013 Oncology
<\/span>Department:<\/span><\/b> <\/span>Operations \- Health Economics and Outcomes Research
<\/span>Location:<\/span><\/b> <\/span>Mumbai or Bangalore, India
<\/span>Years of Experience:<\/span><\/b> <\/span>5\-8 years
<\/span>Employment Type:<\/span><\/span><\/b> <\/span><\/span><\/span>Full\-time, Permanent<\/span><\/div>
<\/span>Key Relationships
<\/span><\/span><\/b>Vice President \u2013 Operations, Operational Research and Impact Measurement<\/span><\/span><\/div>
<\/span><\/span>Job Description
<\/span><\/span><\/b>Qure.ai is seeking an experienced Clinical Research Scientist to lead the design and execution of high\-quality clinical research studies that generate evidence for our AI\-enabled oncology solutions, with a primary focus on lung health applications in the United States market. This is an India\-based full\-time role focused on research on AI\-enabled novel disease detection pathways within the US healthcare ecosystem. The role will involve developing real\-world evidence and prospective study protocols, supporting peer\-reviewed scientific dissemination, and partnering with pharmaceutical, academic, and health\-system collaborators, including providers and payers across the US.
<\/span><\/span>
<\/span><\/span>This position requires strong scientific rigor, the ability to translate clinical needs into robust study designs, and comfort operating in the interdisciplinary, fast\-paced environments typical of healthcare AI. While prior research experience in oncology and/or lung health is welcomed, a strong foundation in clinical research methodology combined with a genuine interest in AI applications for oncology is what we are most looking for.
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<\/span><\/span>Roles and Responsibilities
<\/span><\/span><\/b>
<\/span><\/span><\/b>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Support the design and execution of retrospective, prospective, reader, real\-world evidence, validation and implementation studies to demonstrate the clinical utility, real\-world impact, and effectiveness of Qure's AI solutions for early detection and improved patient outcomes.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Develop study protocols, statistical analysis plans, case report forms, and IRB documentation aligned with US clinical practice workflows.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Support real\-world evidence (RWE) studies leveraging US data sources, including claims, electronic health records, and oncology registries, often in partnership with pharmaceutical collaborators and academic medical centers.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Collaborate with Product, Business Development, and R&D teams to ensure clinical studies align with product adoption and market access goals within the US market.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Engage with principal investigators, clinicians, external experts, key opinion leaders, CROs, pharmaceutical stakeholders, and other research partners to validate study designs, ensure rigorous study execution and generate high\-quality evidence for publication.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Conduct data quality review, ground\-truth adjudication processes, study monitoring, and issue resolution in collaboration with clinical, technical and operational stakeholders.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Draft scientific manuscripts, abstracts, posters, conference presentations, white papers, technical reports for dissemination of research findings through publication in peer\-reviewed journals, conference abstracts, posters, and oral presentations at major oncology and imaging meetings.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Conduct targeted and systematic literature reviews to inform study design, protocol development, clinical assumptions, endpoint selection, and publication planning.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Develop and maintain a strong understanding of the US lung health landscape, including relevant clinical guidelines, screening pathways, reimbursement context, and adoption considerations for AI\-enabled technologies.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Help translate research findings and real\-world evidence on clinical and health system outcomes and into clear scientific narratives for external stakeholders, including clinicians, providers, payers, life sciences partners, and policy stakeholders.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Contribute to the development and maintenance of SOPs, study templates, and internal frameworks for clinical research execution at Qure.ai.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Ensure high standards of scientific integrity, documentation, regulatory compliance, and reproducibility across all clinical research outputs.<\/span><\/span><\/div>
<\/div><\/span>
Requirements<\/h3>
<\/span>
<\/span><\/span><\/b>Qure.ai is the world's fastest\-growing medical AI company, boasting an impressive 13 FDA and 62 CE marking clearances to date. We develop cutting\-edge solutions that significantly enhance patient outcomes across various care domains, including lung cancer, tuberculosis, and stroke. Our innovative technologies have positively impacted over 22 million patients in more than 90 countries worldwide. At Qure.ai, we are committed to fostering a diverse and inclusive workplace and are proud to be an equal\-opportunity employer.
<\/span>
<\/span><\/span><\/span>About the job
<\/span><\/span>Job Title:<\/span><\/span><\/b> <\/span><\/span><\/span>Clinical Research Scientist \u2013 Oncology
<\/span>Department:<\/span><\/b> <\/span>Operations \- Health Economics and Outcomes Research
<\/span>Location:<\/span><\/b> <\/span>Mumbai or Bangalore, India
<\/span>Years of Experience:<\/span><\/b> <\/span>5\-8 years
<\/span>Employment Type:<\/span><\/span><\/b> <\/span><\/span><\/span>Full\-time, Permanent<\/span><\/div>
<\/span>Key Relationships
<\/span><\/span><\/b>Vice President \u2013 Operations, Operational Research and Impact Measurement<\/span><\/span><\/div>
<\/span><\/span>Job Description
<\/span><\/span><\/b>Qure.ai is seeking an experienced Clinical Research Scientist to lead the design and execution of high\-quality clinical research studies that generate evidence for our AI\-enabled oncology solutions, with a primary focus on lung health applications in the United States market. This is an India\-based full\-time role focused on research on AI\-enabled novel disease detection pathways within the US healthcare ecosystem. The role will involve developing real\-world evidence and prospective study protocols, supporting peer\-reviewed scientific dissemination, and partnering with pharmaceutical, academic, and health\-system collaborators, including providers and payers across the US.
<\/span><\/span>
<\/span><\/span>This position requires strong scientific rigor, the ability to translate clinical needs into robust study designs, and comfort operating in the interdisciplinary, fast\-paced environments typical of healthcare AI. While prior research experience in oncology and/or lung health is welcomed, a strong foundation in clinical research methodology combined with a genuine interest in AI applications for oncology is what we are most looking for.
<\/span><\/span>
<\/span><\/span>
<\/span><\/span>Roles and Responsibilities
<\/span><\/span><\/b>
<\/span><\/span><\/b>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Support the design and execution of retrospective, prospective, reader, real\-world evidence, validation and implementation studies to demonstrate the clinical utility, real\-world impact, and effectiveness of Qure's AI solutions for early detection and improved patient outcomes.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Develop study protocols, statistical analysis plans, case report forms, and IRB documentation aligned with US clinical practice workflows.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Support real\-world evidence (RWE) studies leveraging US data sources, including claims, electronic health records, and oncology registries, often in partnership with pharmaceutical collaborators and academic medical centers.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Collaborate with Product, Business Development, and R&D teams to ensure clinical studies align with product adoption and market access goals within the US market.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Engage with principal investigators, clinicians, external experts, key opinion leaders, CROs, pharmaceutical stakeholders, and other research partners to validate study designs, ensure rigorous study execution and generate high\-quality evidence for publication.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Conduct data quality review, ground\-truth adjudication processes, study monitoring, and issue resolution in collaboration with clinical, technical and operational stakeholders.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Draft scientific manuscripts, abstracts, posters, conference presentations, white papers, technical reports for dissemination of research findings through publication in peer\-reviewed journals, conference abstracts, posters, and oral presentations at major oncology and imaging meetings.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Conduct targeted and systematic literature reviews to inform study design, protocol development, clinical assumptions, endpoint selection, and publication planning.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Develop and maintain a strong understanding of the US lung health landscape, including relevant clinical guidelines, screening pathways, reimbursement context, and adoption considerations for AI\-enabled technologies.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Help translate research findings and real\-world evidence on clinical and health system outcomes and into clear scientific narratives for external stakeholders, including clinicians, providers, payers, life sciences partners, and policy stakeholders.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Contribute to the development and maintenance of SOPs, study templates, and internal frameworks for clinical research execution at Qure.ai.
<\/span><\/span>\u2022 <\/span><\/span><\/span><\/span><\/span><\/span>Ensure high standards of scientific integrity, documentation, regulatory compliance, and reproducibility across all clinical research outputs.<\/span><\/span><\/div>
<\/div><\/span>
Requirements<\/h3><\/span><\/span><\/b>
<\/span><\/span><\/span>\- Master's degree (minimum) in a relevant discipline such as Clinical Research, Epidemiology, Biostatistics, Translational Science or a related quantitative field; candidates with MD, MD\-PhD, or PhD qualifications are strongly encouraged to apply.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>5\u20138 years of relevant experience in clinical research, real\-world evidence generation, or evidence\-based medicine within pharmaceutical, medical device, CRO, academic, or healthcare AI environments.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Demonstrated experience designing and executing clinical research studies, including protocol development, endpoint definition, study documentation, statistical analysis, and manuscript writing.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Familiarity with study designs across observational, prospective cohort studies, randomized controlled trials, and real\-world evidence methodologies.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Direct experience supporting US\-based clinical research and working knowledge of the US healthcare context is a strong advantage.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Demonstrated Proficiency in Python or R or similar tools for statistical analysis.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Strong grasp of bio statistics including sample size calculations and advanced statistical analysis, especially in multi\-centre study designs.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Demonstrated scientific writing skills with a track record of peer\-reviewed publications, conference proceedings, or other academic outputs.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Familiarity with oncology clinical pathways is desirable, however candidates with strong clinical research foundations and a genuine interest in AI applications for oncology and lung health will be given equal consideration.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Excellent project management and multi\-tasking abilities; ability to own study timelines and budgets and to coordinate across multiple internal teams and external stakeholders.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Experience working with global, cross\-functional teams; strong presentation and communication skills, with the ability to translate complex clinical and statistical concepts for non\-technical audiences.<\/span><\/span>
\u2022
<\/span><\/span><\/span>\- Master's degree (minimum) in a relevant discipline such as Clinical Research, Epidemiology, Biostatistics, Translational Science or a related quantitative field; candidates with MD, MD\-PhD, or PhD qualifications are strongly encouraged to apply.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>5\u20138 years of relevant experience in clinical research, real\-world evidence generation, or evidence\-based medicine within pharmaceutical, medical device, CRO, academic, or healthcare AI environments.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Demonstrated experience designing and executing clinical research studies, including protocol development, endpoint definition, study documentation, statistical analysis, and manuscript writing.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Familiarity with study designs across observational, prospective cohort studies, randomized controlled trials, and real\-world evidence methodologies.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Direct experience supporting US\-based clinical research and working knowledge of the US healthcare context is a strong advantage.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Demonstrated Proficiency in Python or R or similar tools for statistical analysis.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Strong grasp of bio statistics including sample size calculations and advanced statistical analysis, especially in multi\-centre study designs.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Demonstrated scientific writing skills with a track record of peer\-reviewed publications, conference proceedings, or other academic outputs.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Familiarity with oncology clinical pathways is desirable, however candidates with strong clinical research foundations and a genuine interest in AI applications for oncology and lung health will be given equal consideration.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Excellent project management and multi\-tasking abilities; ability to own study timelines and budgets and to coordinate across multiple internal teams and external stakeholders.<\/span><\/span>
\u2022 <\/span><\/span><\/span><\/span>Experience working with global, cross\-functional teams; strong presentation and communication skills, with the ability to translate complex clinical and statistical concepts for non\-technical audiences.<\/span><\/span>
\u2022