Research Assistant/Associate in Exoplanetary Remote Sensing and Data Science (up to 2 posts) (F[...]

University of Cambridge
Cambridge
20 hours ago
Create job alert
Research Assistant/Associate in Exoplanetary Remote Sensing and Data Science (up to 2 posts) (Fixed Term)

Fixed-term: The appointment will be made for two years in the first instance, with the possibility for extension up to one year. This UKRI‑funded postdoctoral position is at the Institute of Astronomy, University of Cambridge, within the research group of Prof. Nikku Madhusudhan. The group has extensive expertise in exoplanetary science across atmospheres, interiors and habitability, in both observational and theoretical areas.


The position will focus on characterising low‑mass exoplanets in the sub‑Neptune regime using observations with the James Webb Space Telescope (JWST) and other facilities. One or more posts will be available in areas related to exoplanetary remote sensing and data science, including data reduction and analyses, statistical methods and software development.



  • Strong expertise in one or more of the following areas:

    • Astronomical spectroscopy, preferably exoplanet spectroscopy using HST, JWST, large ground‑based telescopes and/or other facilities at low or high resolution, including data reduction and time‑series analyses.
    • Earth or planetary remote sensing.
    • Data science approaches, including statistical methods, handling of large datasets, pipeline development and/or machine learning.
    • Full‑stack software development in relevant applications, including system analysis, design, implementation, testing and deployment.



Candidates with limited experience in exoplanetary science but with strong relevant expertise in the areas listed above are welcome to apply. Applicants must have a PhD in Astronomy, Physics, Computer Science, Engineering or a related field, or have satisfied the requirements for PhD by the time of appointment.


Successful candidates will be expected to pursue a competitive research programme in a collegial environment and have strong communication and computing skills. A successful candidate with a PhD will be appointed at Grade 7 (£37,694 to £46,049 per annum). A candidate who has not been awarded their PhD will initially be appointed at Grade 5 (£34,610 to £35,608 per annum) and, upon award of PhD, promoted to Grade 7.


The University of Cambridge thrives on the diversity of its staff and students. Applications from under‑represented groups are particularly welcome. The University has a number of family‑friendly policies and initiatives, including a returning‑career scheme, childcare costs support, university workplace nurseries, university holiday play‑schemes and a shared parental‑leave policy. As part of its commitment to providing a family‑friendly environment for researchers, the IoA ensures that should parental leave be needed during the course of employment, there is provision for extension to contract to compensate for the parental leave taken.


Please quote reference LG48101 on your application and in any correspondence about this vacancy. Further particulars are available on the recruitment portal. For any queries regarding the application please contact:



  • HR:
  • Informal inquiries may be addressed to Professor Nikku Madhusudhan via

The University of Cambridge is a signatory of the San Francisco Declaration on Research Assessment (DORA). 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/.


The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. The University has a responsibility to ensure that all employees are eligible to live and work in the UK. This role is supported by a UKRI Frontier Grant.


The application deadline is 23:59 GMT on Sunday, 11th January 2026. Interviews will be provisionally scheduled for early February. The start date of the appointment is negotiable.


Seniority level

  • Internship

Employment type

  • Contract

Job function

  • Research, Analyst, and Information Technology
  • Industries: Research Services


#J-18808-Ljbffr

Related Jobs

View all jobs

Exoplanetary Remote Sensing & Data Science Postdoc

Assistant/Associate Professor, Air Quality & Data Science

Machine Learning Engineer

Benefits & HR Systems Data Analyst

Senior Data Scientist

Hybrid Medical Data Science Research Assistant

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Jobs

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Jobs

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.