Research Assistant / Associate: Cosmological Simulation Based Inference (up to 3 posts) (Fixed Term)

Applications are invited for up to three Postdoctoral Research Associate positions to support an ambitious research programme at the University of Cambridge, focusing on cosmological data analysis using cutting-edge AI techniques. The successful candidates will join a vibrant team led by Will Handley, dedicated to harnessing advanced methodologies such as simulation-based inference, Bayesian forecasting, and experimental design to extract maximal information from next-generation cosmological surveys and experiments. Our research spans a range of cosmological probes, including the Cosmic Microwave Background (CMB), Baryon Acoustic Oscillations (BAO), weak lensing, and gravitational wave data. These positions offer a higher than usual level of research freedom, allowing candidates to tailor their projects according to their interests and expertise while leveraging the strengths of the Cambridge cosmology cluster. Researchers with theoretical inclinations will have opportunities to develop models collaboratively with theorists within the Cambridge community. The postholders will be expected to:

• Develop and apply advanced Bayesian & AI techniques, including simulation-based inference and leveraging new AI tools exemplified by large language models (e.g., GPT, Claude, Gemini), to enhance the scientific discovery process.
• Be responsive to emerging techniques, tensions, and data, addressing key issues such as the Hubble tension, weak lensing discrepancies, curvature constraints, and evolving dark energy scenarios.
• Analyze data from various cosmological probes according to their expertise, contributing to projects that may vary over time.
• Collaborate closely with team members and engage with the wider Cambridge cosmology community, fostering interdisciplinary research.
• Contribute to the supervision and mentoring of PhD and Masters students, as well as summer students, supporting a dynamic learning environment.
• Stay abreast of advancements in AI and cosmology to ensure the research group remains at the cutting edge of these disciplines.
  
  We are seeking to appoint candidates of the highest calibre to contribute to this transformative research initiative. The successful applicants will have a strong background in cosmology, astrophysics, or a related field, and experience with AI techniques is highly desirable. This is an excellent opportunity to engage in pioneering research within a world-leading institution and to make significant contributions to our understanding of the Universe., Applicants must have a PhD in Astronomy or related field. Applicants must possess a scientific publication record and a clear outline of current/future research areas. Applicants must have excellent communication and computing skills.
The appointment will be at Grade 7 (Research Associate) £36,924 - £45,163 p.a. (Grade 7, Pts 41-48), depending on experience/qualifications.
• A successful candidate not yet awarded a PhD will be appointed at Grade 5 (Research Assistant) £33,882 - £34,866 (Grade 5, Pts 38-39) and amended to Research Associate (Grade 7) upon confirmation of PhD.
The post is full-time, but applications are welcome from those who would like to work flexibly. Conversations about flexible working are encouraged at the University of Cambridge. Please feel free to discuss flexibility prior to applying (using the contact information below) or at interview if your application is successful.

The University of Cambridge is a signatory of the San Francisco Declaration on Research Assessment (DORA). DORA recognises the need to improve the ways in which the outputs of scholarly research are evaluated. The University expects candidates to apply the principles of DORA when preparing their applications. We do not use journal-level metrics when assessing the quality of research outputs. Applicants should not include journal-level metrics, such as the Journal Impact Factor, anywhere in their application materials. More information about DORA, its principles and aims can be found at: https://sfdora.org/ and https://www.research-strategy.admin.cam.ac.uk/research-policy/DORA.