119 molecular-modeling-or-molecular-dynamic-simulation positions at University of London
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Infectious Disease Epidemiology & Dynamics department at LSHTM to work on polio eradication. This role utilises global surveillance data for polio to inform understanding of the status of eradication and
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and/or evolutionary biology, with significant experience in embryological methods, single-cell/nuclei approaches, and general molecular biology techniques. A track record of high-quality published
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in partnership to achieve excellence in public and global health research, education and translation of knowledge into policy and practice. The Department of Infectious Disease Epidemiology & Dynamics
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of software related to own area of specialism, with the ability to build basic models or tools. Sound working knowledge of policies, regulations and legislation in area of specialism. Excellent analytical and
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About the Role The combination of personalised biophysical models and deep learning techniques with a digital twin approach has the potential to generate new treatments for cardiac diseases. Our
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, ServiceNow, Adobe Marketo Engage, EvaSys, Dynamics and more whilst ensuring data integrity and continuity through system changes and upgrades. The role also involves sourcing and integrating datasets, applying
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delivers measurable value. You will lead a high-performing team to build advanced analytics capabilities, including propensity modeling, marketing mix modeling (MMM), incrementality testing, and multi-touch
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of our clients. We are seeking 2 dynamic Senior Account Manager to join our team and drive the seamless delivery of custom programmes. As a pivotal commercial project leader, the Senior Account Manager is
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, conducting simulation studies, analysis of datasets from economic and social research studies, software implementation and delivery of workshops. The Research Fellow will be supervised by Prof. Jonathan
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responsibilities will include: Pre-registering data analysis plans; Leading and conducting advanced statistical analyses (e.g., twin/family designs, genomic and epidemiological methods, longitudinal modelling