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Research Fellow in Early-Phase and Digital Health Trial Statistics
RFCSR
Research Fellow in Early-Phase and Digital Health Trial Statistics King's College London London, United Kingdom This position invites a dynamic researcher to join the Unit for Medical Statistics within the School of Life Course & Population Sciences at King's College London. It focuses on advanced statistical contributions to cutting-edge clinical trials and digital health research, especially in early-phase trials, studies involving digital health technologies, real-world data and translational methodologies. As part of a multidisciplinary team, the successful candidate will engage with statistical components across the entire trial lifecycle - from trial design and protocol documentation to statistical analysis planning, interim and final analyses, and regulatory reporting. This role plays a key part in ensuring that emerging health interventions and digital innovations are supported by robust, rigorous statistical strategy and execution. The post is offered on a full-time, fixed-term contract until 2 March 2028, reflecting long-term engagement in impactful research projects. Eligibility Criteria PhD in Medical Statistics, Biostatistics, Mathematics, Epidemiology or a closely related quantitative discipline with relevant postdoctoral experience. Demonstrated experience in statistical work for clinical trials and quantitative health research. Understanding of clinical trial phases and regulatory frameworks such as Good Clinical Practice (GCP). Strong programming capabilities using statistical packages such as R, Stata, Python. Required Expertise & Skills Ability to contribute to statistical elements of trial protocols, randomization strategies, statistical analysis plans, and reporting. Experience analysing clinical trial data and adapting statistical methodology to complex research designs. Capacity to work collaboratively within multidisciplinary teams while also providing independent scientific input. A track record of academic publication in clinical trials or methodology and experience contributing to research funding proposals is expected. Annual salary ranges from £53,947 to £63,350, inclusive of London Weighting Allowance. Applications close on 11 March 2026.
Sep 27, 2026
Full time
Research Fellow in Early-Phase and Digital Health Trial Statistics King's College London London, United Kingdom This position invites a dynamic researcher to join the Unit for Medical Statistics within the School of Life Course & Population Sciences at King's College London. It focuses on advanced statistical contributions to cutting-edge clinical trials and digital health research, especially in early-phase trials, studies involving digital health technologies, real-world data and translational methodologies. As part of a multidisciplinary team, the successful candidate will engage with statistical components across the entire trial lifecycle - from trial design and protocol documentation to statistical analysis planning, interim and final analyses, and regulatory reporting. This role plays a key part in ensuring that emerging health interventions and digital innovations are supported by robust, rigorous statistical strategy and execution. The post is offered on a full-time, fixed-term contract until 2 March 2028, reflecting long-term engagement in impactful research projects. Eligibility Criteria PhD in Medical Statistics, Biostatistics, Mathematics, Epidemiology or a closely related quantitative discipline with relevant postdoctoral experience. Demonstrated experience in statistical work for clinical trials and quantitative health research. Understanding of clinical trial phases and regulatory frameworks such as Good Clinical Practice (GCP). Strong programming capabilities using statistical packages such as R, Stata, Python. Required Expertise & Skills Ability to contribute to statistical elements of trial protocols, randomization strategies, statistical analysis plans, and reporting. Experience analysing clinical trial data and adapting statistical methodology to complex research designs. Capacity to work collaboratively within multidisciplinary teams while also providing independent scientific input. A track record of academic publication in clinical trials or methodology and experience contributing to research funding proposals is expected. Annual salary ranges from £53,947 to £63,350, inclusive of London Weighting Allowance. Applications close on 11 March 2026.
Brain Research UK Miriam Marks Postdoctoral Research Fellow in Neurodegenerative Diseases
RFCSR
Brain Research UK Miriam Marks Postdoctoral Research Fellow in Neurodegenerative Diseases University College London (UCL) London, United Kingdom University College London (UCL) is seeking to appoint a Brain Research UK Miriam Marks Postdoctoral Research Fellow in Neurodegenerative Diseases. This prestigious fellowship is designed to support high-quality, innovative research aimed at advancing understanding of neurodegenerative disorders. The position is based within UCL's world-leading research environment, offering access to cutting-edge facilities and opportunities for interdisciplinary collaboration. The successful candidate will undertake independent and collaborative research focused on neurodegenerative diseases, contributing to the development of novel approaches to understanding disease mechanisms and potential therapeutic strategies. Responsibilities include designing and conducting experiments, analyzing complex datasets, preparing high-impact publications, and presenting findings at national and international conferences. The role may also involve mentoring junior researchers and contributing to grant applications and broader academic activities within the department. This fellowship reflects UCL's commitment to advancing neuroscience research and supporting early-career researchers in establishing independent research trajectories. The position offers a stimulating academic environment with strong institutional support for professional development and career progression. Eligibility Criteria: Applicants must hold a PhD in neuroscience, neurobiology, or a closely related discipline. Candidates should demonstrate a strong track record of research excellence in neurodegenerative diseases or related areas. Required expertise/skills: Candidates should possess advanced knowledge of neurodegenerative disease research, including experimental design and data analysis. Strong laboratory skills, experience with relevant research methodologies, and proficiency in handling complex biological data are essential. Excellent written and verbal communication skills are required, along with a proven ability to publish in peer-reviewed journals. The ability to work independently and collaboratively in a multidisciplinary research environment is essential. Salary details: £42,099 to £50,585 per annum (depending on experience).
Sep 27, 2026
Full time
Brain Research UK Miriam Marks Postdoctoral Research Fellow in Neurodegenerative Diseases University College London (UCL) London, United Kingdom University College London (UCL) is seeking to appoint a Brain Research UK Miriam Marks Postdoctoral Research Fellow in Neurodegenerative Diseases. This prestigious fellowship is designed to support high-quality, innovative research aimed at advancing understanding of neurodegenerative disorders. The position is based within UCL's world-leading research environment, offering access to cutting-edge facilities and opportunities for interdisciplinary collaboration. The successful candidate will undertake independent and collaborative research focused on neurodegenerative diseases, contributing to the development of novel approaches to understanding disease mechanisms and potential therapeutic strategies. Responsibilities include designing and conducting experiments, analyzing complex datasets, preparing high-impact publications, and presenting findings at national and international conferences. The role may also involve mentoring junior researchers and contributing to grant applications and broader academic activities within the department. This fellowship reflects UCL's commitment to advancing neuroscience research and supporting early-career researchers in establishing independent research trajectories. The position offers a stimulating academic environment with strong institutional support for professional development and career progression. Eligibility Criteria: Applicants must hold a PhD in neuroscience, neurobiology, or a closely related discipline. Candidates should demonstrate a strong track record of research excellence in neurodegenerative diseases or related areas. Required expertise/skills: Candidates should possess advanced knowledge of neurodegenerative disease research, including experimental design and data analysis. Strong laboratory skills, experience with relevant research methodologies, and proficiency in handling complex biological data are essential. Excellent written and verbal communication skills are required, along with a proven ability to publish in peer-reviewed journals. The ability to work independently and collaboratively in a multidisciplinary research environment is essential. Salary details: £42,099 to £50,585 per annum (depending on experience).
Postdoctoral Research Fellow - Genomics, AI & Synthetic Biology
Ellison Institute, LLC Oxford, Oxfordshire
Ellison Institute of Technology in Oxford is building a joint experimental computational team focused on creating, training and validating multi-modal biological models. The team will generate perturbation data at scale, build models, and use data to train and validate methods. You will perform genome engineering and design scalable measurement across modalities with automation support. You will join AI scientists and synthetic biologists working together to push biology at scale and translate
Sep 14, 2026
Full time
Ellison Institute of Technology in Oxford is building a joint experimental computational team focused on creating, training and validating multi-modal biological models. The team will generate perturbation data at scale, build models, and use data to train and validate methods. You will perform genome engineering and design scalable measurement across modalities with automation support. You will join AI scientists and synthetic biologists working together to push biology at scale and translate
Postdoctoral Research Fellow (Chin Lab) - Generative Biology Institute Generative Biology Institute Oxford, England, United Kingdom
Ellison Institute, LLC Oxford, Oxfordshire
At the Ellison Institute of Technology (EIT), we're on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, engineers, researchers, educators and innovators to tackle humanity's greatest challenges in four transformative areas: Health, Medical Science & Generative Biology Food Security & Sustainable Agriculture Climate Change & Managing CO Artificial Intelligence & Robotics This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you'll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Together, we push boundaries, embrace complexity, and create solutions to scale ideas from lab to society. Welcome to the Generative Biology Institute: Led by Founding Director Jason Chin, the Generative Biology Institute (GBI) at the Ellison Institute of Technology is tackling the key challenges in making biology engineerable, and thereby releasing the unrivalled power of biology for the benefit of humanity. The vision of GBI is to lay the foundations for engineering biology, and unlock its potential for good. To achieve this, we must overcome two key challenges. First, we need the ability to write in the natural language of biology, enabling the rapid and scalable synthesis of entire genomes with precision. Second, we must understand what to write - determining which DNA sequences will generate biological systems that perform the desired functions. Addressing these challenges will allow us to harness the full power of biology to create transformative solutions across health, agriculture, clean energy and more. The Generative Biology Institute commenced operations in 2025, occupying newly renovated bespoke space in the Oxford Science Park. The team will later move to a purpose-made facility in the Oxford Science Park, currently under construction. Once complete, this state-of-the-art facility will include more than 40,000 m of research laboratory and office space. It will house over 30 groups and up to 600 employees at scale, focused on solving the two critical challenges in making biology engineerable and applying the solutions to addressing the global challenges encapsulated in EIT's Humane Endeavours. Job Summary We are building a joint experimental computational team focussed on building, training and validating multi-modal biological models. The team will: i) generate experimental perturbation and measurement data at scale, ii) build multi-modal biological models and, iii) use the experimental data they generate to train and validate the multi-modal biological models they build. In this role you will: i) perform experimental genome engineering work to generate genetic variation at scale and/or ii) design and implement scalable biological measurement over one or more modalities. Where appropriate the work will leverage the substantial automation capability within the institute. Your work will be performed under the guidance of Jason Chin. You will be part of a single team composed of AI scientists and synthetic biologists working together. We are looking for colleagues with deep expertise in genome engineering and/or quantitative phenotyping of model bacterial species such as Escherichia coli. The role requires the ability and willingness to work as part of a cross-disciplinary team at the interface of computational and wetlab biology. Our team ethos is based on mutual learning, strong peer-to-peer support, and a deep sense of scientific curiosity and ambition. This is your opportunity to be part of cutting-edge research within an institute dedicated to engineering biology at an unprecedented scale. You will be leveraging GBI's exceptional facilities, sustained funding, and collaborative environment. You will design and execute experiments, contribute to high-impact publications, and play a key role in the training and mentorship of junior researchers and students. Working at the interface of biology, AI, technology, and engineering, you will help shape GBI's vision to reimagine what's possible in biology. Key Responsibilities: Design, execute, and troubleshoot experiments, including the development of novel methodologies and adaptation of existing techniques to new applications. In particular, the successful applicant will utilise genome engineering strategies in the lab to produce a diversity of microbial strains as the source of training and validation data in a high throughput fashion. In addition, they will also design and prototype a range of experimental measurement strategies for characterising these strains at scale. Collaborate with other GBI scientists from other groups expert in synthetic biology, automation, bioinformatics, -omics and machine learning, and AI scientists from the AIR institute, as required. Analyse complex datasets using computational and statistical tools, interpreting results in the context of broader research goals. Contribute intellectually to the research direction by identifying opportunities for innovation and refining research questions. Prepare and publish high-quality scientific papers, reports, presentations, and protocols. Present research at national and international conferences, seminars, and internal meetings. Collaborate with multidisciplinary teams within GBI, EIT, and external partners to advance complementary workstreams. Build and maintain research infrastructure, laboratory capabilities, and cutting-edge technologies. Mentor and support junior researchers, including PhD students and research assistants. Translate research findings into commercial or translational opportunities in alignment with EIT's mission. Identify and pursue opportunities for intellectual property generation and protection.Ensure research activities comply with EIT's policies, legal requirements, and best scientific practice. This list is not exhaustive and the role holder may be required to undertake additional tasks and duties commensurate with the role. Relevant, Skills and Experience: Completed a PhD in a relevant field (e.g., synthetic biology, computational biology and AI, microbial genomics, cell biology, genomics, robotics and automation, metabolomics, and proteomics.). Track record of delivering ambitious research projects to a high standard. Strong track record in research, ideally in molecular biology, synthetic biology, or related fields. Skilled in data analysis and interpretation; experience with genomic analysis, automation, or computational tools desirable. Proven ability to work independently, think creatively, and solve complex experimental problems. Experience publishing in high-impact journals and presenting at international conferences. Excellent organisational skills with the ability to manage multiple concurrent projects. Strong written and verbal communication skills, with experience collaborating in multidisciplinary teams. Capacity to build and sustain productive collaborations internally and externally. Resilience, adaptability, and enthusiasm for working in a fast paced, high growth research environment. Our Benefits: Annual Bonus Travel allowance Enhanced sick pay Pension - Employer contribution 7.5%, minimum employee contribution 5% Life Assurance Income Protection Private Medical Insurance as standard for you, your partner and any dependents. Including hospital Cash Plan Employee discounts Electric car scheme Nursery Salary Sacrifice scheme Cycle to Work Scheme Family Planning Neurodiversity support including advise and assessments Coaching & Therapy services Working Together - What It Involves: You must have the right to work permanently in the UK with a willingness to travel as necessary. In certain cases, we can consider sponsorship, and this will be assessed on a case-by-case basis. You will live in, or within easy commuting distance of, Oxford (or be willing to relocate).
Sep 14, 2026
Full time
At the Ellison Institute of Technology (EIT), we're on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, engineers, researchers, educators and innovators to tackle humanity's greatest challenges in four transformative areas: Health, Medical Science & Generative Biology Food Security & Sustainable Agriculture Climate Change & Managing CO Artificial Intelligence & Robotics This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you'll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Together, we push boundaries, embrace complexity, and create solutions to scale ideas from lab to society. Welcome to the Generative Biology Institute: Led by Founding Director Jason Chin, the Generative Biology Institute (GBI) at the Ellison Institute of Technology is tackling the key challenges in making biology engineerable, and thereby releasing the unrivalled power of biology for the benefit of humanity. The vision of GBI is to lay the foundations for engineering biology, and unlock its potential for good. To achieve this, we must overcome two key challenges. First, we need the ability to write in the natural language of biology, enabling the rapid and scalable synthesis of entire genomes with precision. Second, we must understand what to write - determining which DNA sequences will generate biological systems that perform the desired functions. Addressing these challenges will allow us to harness the full power of biology to create transformative solutions across health, agriculture, clean energy and more. The Generative Biology Institute commenced operations in 2025, occupying newly renovated bespoke space in the Oxford Science Park. The team will later move to a purpose-made facility in the Oxford Science Park, currently under construction. Once complete, this state-of-the-art facility will include more than 40,000 m of research laboratory and office space. It will house over 30 groups and up to 600 employees at scale, focused on solving the two critical challenges in making biology engineerable and applying the solutions to addressing the global challenges encapsulated in EIT's Humane Endeavours. Job Summary We are building a joint experimental computational team focussed on building, training and validating multi-modal biological models. The team will: i) generate experimental perturbation and measurement data at scale, ii) build multi-modal biological models and, iii) use the experimental data they generate to train and validate the multi-modal biological models they build. In this role you will: i) perform experimental genome engineering work to generate genetic variation at scale and/or ii) design and implement scalable biological measurement over one or more modalities. Where appropriate the work will leverage the substantial automation capability within the institute. Your work will be performed under the guidance of Jason Chin. You will be part of a single team composed of AI scientists and synthetic biologists working together. We are looking for colleagues with deep expertise in genome engineering and/or quantitative phenotyping of model bacterial species such as Escherichia coli. The role requires the ability and willingness to work as part of a cross-disciplinary team at the interface of computational and wetlab biology. Our team ethos is based on mutual learning, strong peer-to-peer support, and a deep sense of scientific curiosity and ambition. This is your opportunity to be part of cutting-edge research within an institute dedicated to engineering biology at an unprecedented scale. You will be leveraging GBI's exceptional facilities, sustained funding, and collaborative environment. You will design and execute experiments, contribute to high-impact publications, and play a key role in the training and mentorship of junior researchers and students. Working at the interface of biology, AI, technology, and engineering, you will help shape GBI's vision to reimagine what's possible in biology. Key Responsibilities: Design, execute, and troubleshoot experiments, including the development of novel methodologies and adaptation of existing techniques to new applications. In particular, the successful applicant will utilise genome engineering strategies in the lab to produce a diversity of microbial strains as the source of training and validation data in a high throughput fashion. In addition, they will also design and prototype a range of experimental measurement strategies for characterising these strains at scale. Collaborate with other GBI scientists from other groups expert in synthetic biology, automation, bioinformatics, -omics and machine learning, and AI scientists from the AIR institute, as required. Analyse complex datasets using computational and statistical tools, interpreting results in the context of broader research goals. Contribute intellectually to the research direction by identifying opportunities for innovation and refining research questions. Prepare and publish high-quality scientific papers, reports, presentations, and protocols. Present research at national and international conferences, seminars, and internal meetings. Collaborate with multidisciplinary teams within GBI, EIT, and external partners to advance complementary workstreams. Build and maintain research infrastructure, laboratory capabilities, and cutting-edge technologies. Mentor and support junior researchers, including PhD students and research assistants. Translate research findings into commercial or translational opportunities in alignment with EIT's mission. Identify and pursue opportunities for intellectual property generation and protection.Ensure research activities comply with EIT's policies, legal requirements, and best scientific practice. This list is not exhaustive and the role holder may be required to undertake additional tasks and duties commensurate with the role. Relevant, Skills and Experience: Completed a PhD in a relevant field (e.g., synthetic biology, computational biology and AI, microbial genomics, cell biology, genomics, robotics and automation, metabolomics, and proteomics.). Track record of delivering ambitious research projects to a high standard. Strong track record in research, ideally in molecular biology, synthetic biology, or related fields. Skilled in data analysis and interpretation; experience with genomic analysis, automation, or computational tools desirable. Proven ability to work independently, think creatively, and solve complex experimental problems. Experience publishing in high-impact journals and presenting at international conferences. Excellent organisational skills with the ability to manage multiple concurrent projects. Strong written and verbal communication skills, with experience collaborating in multidisciplinary teams. Capacity to build and sustain productive collaborations internally and externally. Resilience, adaptability, and enthusiasm for working in a fast paced, high growth research environment. Our Benefits: Annual Bonus Travel allowance Enhanced sick pay Pension - Employer contribution 7.5%, minimum employee contribution 5% Life Assurance Income Protection Private Medical Insurance as standard for you, your partner and any dependents. Including hospital Cash Plan Employee discounts Electric car scheme Nursery Salary Sacrifice scheme Cycle to Work Scheme Family Planning Neurodiversity support including advise and assessments Coaching & Therapy services Working Together - What It Involves: You must have the right to work permanently in the UK with a willingness to travel as necessary. In certain cases, we can consider sponsorship, and this will be assessed on a case-by-case basis. You will live in, or within easy commuting distance of, Oxford (or be willing to relocate).

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