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- Artificial Intelligence (AI)
- Queen Mary University of London
- Artificial Intelligence in the Biosciences MSc
Course options
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Qualification
MSc - Master of Science
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Location
Mile End
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Study mode
Full time
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Start date
15-SEP-25
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Duration
1 year
Course summary
Applications of Artificial Intelligence (AI) tools in the biosciences are rapidly expanding and bioscientists skilled in the methods and thinking in AI are in short supply. This programme aims to prepare bioscience graduates to become leaders in the application of AI methods in professional bioscience Research and Development workplace environments. It has been specifically designed to make AI and related computational techniques (machine learning, analysis of large data sets) accessible to biology and biomedical graduate students without any prior experience in computational methods.
- No background in computational methods needed – Learn coding, advanced statistical methods, the handling of large data sets, and applications of AI tools across biology
- Develop in demand technical skills for a field that is rapidly growing in importance
- Strong emphasis of hands-on experience in computer labs and projects using Queen Marys high performance computing cluster, Apocrita
- Be taught by experts in the field, actively engaged in research in this exciting new area - Programme Director Dr Mohamed Elbadawi research centres on the use of digital technologies to advance healthcare, including machine learning, robotics and 3D printing
- Queen Mary is a member of the Alan Turing Institute and host of the Digital Environment Research Institute (DERI), which is amongst the UK's leaders in the development and application of Artificial Intelligence
- Our London location, the hub of the UK AI industry, will place you in prime position for getting a job in the sector when you graduate
- Graduates of this program will be well-positioned to seize the abundant job opportunities in the rapidly growing field of Artificial Intelligence.
- The program will provide abundant opportunities for students to network with peers who possess diverse interests and aspirations
What you'll study
This multifaceted programme builds the knowledge and skills needed to kick-start your career in professional bioscience research, consulting, and development. Teaching is jointly delivered by experts in the School of Biological and Behavioural Sciences and The School of Mathematical Sciences and will cover areas such as applications of AI and Data Science in Biology, Ecology and Biomedicine and skills such as analysis of large data sets, coding, and statistics.
In Semester A you will cover modules on essential shell command and HPC usage, coding, its use for statistical data analysis, and then an introduction to AI concepts, while also discussing applications in bioinformatics.
In Semester B youll be introduced to the full range of applications of AI in the biosciences, covering both established methods and latest cutting-edge developments and trends. You will also cover modern computation-intensive statistical methods.
In Semester C, you will carry out two group projects, solving problems in the biosciences using AI methods to develop your AI knowledge into professional skills. The task in the first project is well defined, so you can focus on learning how to structure a problem to approach it efficiently as a group. Then, for the second project you will be given a more widely defined bioscience problem, emulating a typical work-place situation.
Application deadline
09 September 2024
Modules
Tuition fees
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£ 29,950per year
Tuition fees shown are for indicative purposes and may vary. Please check with the institution for most up to date details.
University information

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University League Table
50th
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Campus address
Queen Mary University of London, Admissions and Recruitment Office, Mile End Road, London, Tower Hamlets, E1 4NS, England
Subject rankings
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Subject ranking
32nd out of 94 8
27th out of 117 4
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Entry standards
/ Max 228141 62%38th
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Graduate prospects
/ Max 10075.0 75%52nd
14 -
Student satisfaction
/ Max 43.06 76%52nd
24 -
Entry standards
/ Max 227151 66%32nd
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Graduate prospects
/ Max 10083.0 83%52nd
6 -
Student satisfaction
/ Max 43.02 76%52nd
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