Research Assistant/Associate in Machine Learning (Fixed Term)
CompanyUniversity of Cambridge
Location
Cambridge, England, United Kingdom
Employment TypeFull-time
Posted At4/17/2026
UK Visa Sponsorship Analytics
Analytics are greyed out due to low classification confidence (52.0%).
Occupation TypeBusiness and related research professionals
Occupation Code Skill LevelHigher Skilled
Sponsorship Salary Threshold
£41,700
(£21.38 per hour)
Standard minimum applies
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Description
We are seeking a highly motivated Research Assistant/Associate in Machine Learning to join an interdisciplinary project at the University of Cambridge focused on machine-learning-guided antibiotic discovery. The successful candidate will work under the joint supervision of Professor José Miguel Hernández Lobato (Department of Engineering) and Professor Andres Floto (Heart & Lung Research Institute).
The position forms part of a collaborative research programme aiming to define and predict the "permissive chemical space" for antibiotics in the pathogen Klebsiella pneumoniae, integrating high-throughput experimental measurements with state-of-the-art machine learning and generative AI approaches. The project brings together expertise in microbiology, chemistry, genomics, and artificial intelligence to develop predictive models and computational tools that guide the design of new antibiotics. The postholder will contribute to the development of predictive and generative machine learning methods that translate experimental measurements of compound retention and metabolism in bacteria into scalable computational models for drug discovery.
The Research Assistant/Associate will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato, other members of the Cambridge Machine Learning Group (http://mlg.eng.cam.ac.uk/) and Andres Floto and his group members.
Key responsibilities include working on deep learning, deep generative modelling, and molecular design.
Additional responsibilities include developing research objectives and proposals; presentations and publications; assisting with teaching; liaising and networking with colleagues and students; planning and organising research resources and workshops.
Successful applicants must have (or be close to obtaining) a PhD in Computer Science, Information Engineering, Statistics, Chemistry, Biology, or a related area, with extensive research experience and a strong publication record. Excellent mathematical and programming skills are essential, with experience in two or more of deep learning, deep generative models, chemistry, biology.
Interviews are expected to happen in May and June 2026. Applicants are encouraged to guarantee that referees can submit their letters before such date. The interviews will be done via zoom.
Appointment at Research Associate level is dependent on having a PhD in Computer Science, Information Engineering, Statistics, Chemistry, Biology, or a related area. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded.
Salary Ranges
The position forms part of a collaborative research programme aiming to define and predict the "permissive chemical space" for antibiotics in the pathogen Klebsiella pneumoniae, integrating high-throughput experimental measurements with state-of-the-art machine learning and generative AI approaches. The project brings together expertise in microbiology, chemistry, genomics, and artificial intelligence to develop predictive models and computational tools that guide the design of new antibiotics. The postholder will contribute to the development of predictive and generative machine learning methods that translate experimental measurements of compound retention and metabolism in bacteria into scalable computational models for drug discovery.
The Research Assistant/Associate will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato, other members of the Cambridge Machine Learning Group (http://mlg.eng.cam.ac.uk/) and Andres Floto and his group members.
Key responsibilities include working on deep learning, deep generative modelling, and molecular design.
Additional responsibilities include developing research objectives and proposals; presentations and publications; assisting with teaching; liaising and networking with colleagues and students; planning and organising research resources and workshops.
Successful applicants must have (or be close to obtaining) a PhD in Computer Science, Information Engineering, Statistics, Chemistry, Biology, or a related area, with extensive research experience and a strong publication record. Excellent mathematical and programming skills are essential, with experience in two or more of deep learning, deep generative models, chemistry, biology.
Interviews are expected to happen in May and June 2026. Applicants are encouraged to guarantee that referees can submit their letters before such date. The interviews will be done via zoom.
Appointment at Research Associate level is dependent on having a PhD in Computer Science, Information Engineering, Statistics, Chemistry, Biology, or a related area. Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded.
Salary Ranges
Research Assistant: GBP 33,002 - GBP 35,608
Research Associate: GBP 37,694 - GBP 46,049
Fixed-term: The funds for this post are available for 24 months 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 ensure that you upload your Curriculum Vitae (CV), a covering letter and publication list 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 submit your application by midnight on the closing date.
If you have any questions about this vacancy or the application process, please contact Kimberly Cole, email: div-f@eng.cam.ac.uk.
Please quote reference NM49458 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.
Research Associate: GBP 37,694 - GBP 46,049
Fixed-term: The funds for this post are available for 24 months 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 ensure that you upload your Curriculum Vitae (CV), a covering letter and publication list 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 submit your application by midnight on the closing date.
If you have any questions about this vacancy or the application process, please contact Kimberly Cole, email: div-f@eng.cam.ac.uk.
Please quote reference NM49458 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.