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statistical analyses, strong understanding of the strengths and weaknesses of scientific research and / or experience of qualitative research. Expertise will be gained in how to design and conduct a clinical
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-personal communications skills. Desirable skills: Previous experience in medical statistical analyses, strong understanding of the strengths and weaknesses of scientific research and / or experience
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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry
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psychology A successfully completed scientific university degree in psychology Accurate working and strong team spirit Confident handling of large, longitudinal data sets Competent use of statistics and data
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quantitative finance, particularly statistical arbitrage. What are you going to do? You will work 60% of the time on your PhD-project, and 40% of the time on projects at Deep Blue Capital. Those projects will be
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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
state-of-the-art wearable devices. Applicants should have strong experience in data collection in applied settings, advanced statistical analysis skills (particularly in time-series data), and proficiency
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Apply Now Responsibilities* In the field of clinical pain research, design studies and projects to generate preliminary data and develop and implement Statistical Analysis Plans (SAP) for newly
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researchers at the University Centre for Psychiatry. The PhD candidate will work on a philosophical project that covers philosophy of science, statistics and data science, and psychopathology. The PhD project
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 6 hours ago
to perform phenotypic assessment of editing outcomes Analyze experimental data and interprets results. Apply statistical methods to analyze data from experiments, that includes next-generation sequencing data
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. We are looking for highly motivated candidates with a strong academic background in computer science, AI/ML, bioinformatics, or related fields such as mathematics and statistics. Informal enquiries