PhD Fellowships in Chromatography and Mass Spectrometry Targeted and Non-Target Analysis

Overview

The Analytical Chemistry Group at the Department of Plant and Environmental Sciences, University of Copenhagen, invites applications for two PhD fellowships in chromatography, high‑resolution mass spectrometry, and analytical data science. Projects focus on targeted and non‑target analysis of contaminants of emerging concern (CECs) in waste streams and human exposures.

Lead:
Professor Jan H. Christensen (jch.dk). Phone: +45 35 332 456.

Scope:
Characterise micropollutants in wastewater, sludge and advanced treatment processes. Tasks include method development for complex solid matrices, and contribution to hybrid AI–mechanistic models predicting removal efficiency.

Lead:
Associate Professor Nikoline Juul Nielsen (njn.dk). Phone: +45 33 2344.

Scope:
Large‑scale chemical profiling of the urinary exposome and its association with Parkinson’s disease. Work involves method development and validation, compound prioritisation and exposure‑outcome correlation analysis.

State‑of‑the‑art separation science including LC (online‑SPE‑LC), GC×GC, SFC, and high‑resolution MS (Orbitrap, QqTOF, TOF). Analytical data science is central, ranging from chromatographic signal processing to (semi‑)automated compound identification and machine/deep‑learning models.

Expected 1 June 2026 or as soon as possible thereafter.

• MSc in analytical chemistry, environmental analytical chemistry, bio‑analytical chemistry, or a closely related discipline with solid hands‑on experience with LC, GC, or SFC coupled to MS.
• Alternatively, MSc in data science with documented experience modelling complex analytical or mass spectrometric datasets.
• Experience with targeted and/or non‑target screening workflows, including data processing and compound identification.
• Experience working with complex environmental or biological matrices (e.g., wastewater, sludge, urine).
• Experience or interest in method development, validation and quality control of large sample sets.
• Experience with chemometrics, machine learning or deep learning applied to analytical data.
• Programming skills (MATLAB, R, Python) and proven experience in AI‑assisted development with focus on code review and manual optimisation.
• Strong scientific writing and communication skills.
• Ability to work independently, manage research tasks effectively and contribute constructively to a collaborative environment.

• Professional qualifications relevant to the PhD project.
• Relevant publications.
• Relevant work experience.
• Curious mindset with strong interest in analytical chemistry and data processing.
• Good language skills.

• Conduct an independent research project under supervision.
• Complete PhD courses equivalent to approximately 30 ECTS.
• Participate in active research environments, including a stay at another research institution, preferably abroad.
• Engage in teaching and knowledge dissemination activities.
• Write scientific papers targeting high‑impact journals.
• Write and defend a PhD thesis based on the research project.

Submit an application in English electronically, including the following attachments:

• One‑page motivation letter stating the PhD you are applying for.
• Research project proposal (max. 3 pages) choosing one of the two topics.
• Curriculum vitae detailing education, experience, language skills and relevant skills.
• Original diplomas (Bachelor/Master) and transcripts, with authorised English translation if applicable.
• Publication list, if available.
• Reference letters, if available.

Saturday 28th March 2026, 23:59 GMT +1. Applications received after the deadline will not be considered.

Jan H. Christensen – E‑mail: jkx
254

Nikoline Juul Nielsen – E‑mail: gvm
327

The University of Copenhagen wishes to reflect the surrounding community and invites all, regardless of personal background, to apply for the position.