Research Associate in Machine learning for longitudinal population studies with high-dimensional molecular measurements

Institution/Company:
University of Sheffield
Location:
Sheffield, South Yorkshire, United Kingdom
Job Type:
  • Postdoctoral (Up to 3 years)
Degree Level Required:
PhD
Apply Now

Research Associate in Machine learning for longitudinal population studies with high-dimensional molecular measurements

Are you interested in working for a world top 100 university? We have an exciting opportunity in the Department of Computer Science for someone with a passion for machine learning, looking to use their skills in developing novel models for experimental design, analysis and prediction to make an impact on longitudinal population studies with high-dimensional molecular measurements from several international consortiums focusing on public health.

You will join the Machine Learning group in our large and diverse academic department. You will further strengthen our strong international research profile and our reputation for novel, research-led teaching and work in a well-connected team with world-leading reputations in probabilistic modelling, Gaussian processes and open source software. You will have demonstrable knowledge of a wide range of machine learning techniques, in particular, probabilistic modelling and practical experience handling data from longitudinal and/or high-dimensional studies. You will hold a PhD in Computer Science or a related area (or have equivalent experience) with a solid background in mathematics/statistics, excellent scientific programming skills and eagerness to contribute to open source software. If you are passionate about the practical impact of machine learning research, then we would love to hear from you. We’re one of the best not-for-profit organisations to work for in the UK. The University’s Total Reward Package includes a competitive salary, a generous Pension Scheme and annual leave entitlement, as well as access to a range of learning and development courses to support your personal and professional development.

We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience

Responsibilities:

Propose and develop novel machine learning concepts and models to allow the creation of tools which perform experimental design, modelling and analysis of longitudinal and high-dimensional datasets. ● Use best-practice software development methodologies (code repositories, unit testing, etc.) to provide software implementations of high-dimensional longitudinal analysis models, inference procedures and optimal experimental design algorithms. ● Maintain up-to-date knowledge of the relevant literature and organise time to ensure good knowledge of the background of the research area. Particularly machine learning and statistical models for longitudinal and high-dimensional multivariate datasets and scalable inference in probabilistic models. ● Assess and develop pre-processing tools for a variety of data generated by collaborators. ● Apply the pipeline developed to the Pregnancy Outcome Prediction study (POPs), the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Growing Up in Singapore Towards Healthy Outcomes (GUSTO) datasets. ● Validate the performance of the methods developed and compare them against current state-of-the-art design and analysis methods. ● Plan own research activities in discussion with supervisor, incorporating issues such as the availability of resources, deadlines, project milestones and overall research aims. ● Attend project meetings and training events, collaborate and communicate with researchers and other project sites to ensure project progress is maintained. ● Coordinate with other members of the Machine Learning group and the Translational Bioinformatics group to ensure objectives are met. ● Write papers to be presented at conferences and for publication in journals. ● Write supporting documents to contribute to and support the work of the research groups. ● Continuously monitor and check results. The unpredictability of research means that daily planning needs to accommodate new developments

Qualifications:

A PhD in a relevant quantitative discipline, for example computer science, statistics, physics.

Additional Information

All nationalities are welcome to apply. There are multiple routes for immigration and settlement in the UK through this post.

Keywords: