PhD scholarship in Enzyme Discovery, Characterization, and Machine Learning for Micropollutant Degradation - DTU Bioengineering

Jobbeskrivelse

We invite applications for a fully funded PhD position focused on the discovery, characterization, and computational analysis of enzymes capable of degrading urethane-containing micropollutants and microplastic analogs. The project combines bioinformatics, protein biochemistry, structural biology, and machine learning to expand the known family of AS enzymes and understand their substrate specificity.

The successful candidate will work at the interface of computational biology, enzymology, and structural biology, contributing to the development of predictive models linking enzyme sequence, structure, and activity toward environmentally relevant compounds.

Research Objectives

The project aims to:

• Discover and characterize new AS enzyme families from bacterial and fungal genomes.
• Determine enzyme kinetics and stability across environmental conditions.
• Develop machine learning models that predict enzyme–substrate interactions.
• Obtain structural insights into enzyme–micropollutant interactions using crystallography.

Responsibilities and qualifications

Key Responsibilities

1. Enzyme Discovery and Expression

You will:

• Perform bioinformatic mining of genomic databases using BLAST-based searches with known AS enzymes as query sequences.
• Identify homologous candidates based on:
• Presence of signature catalytic motifs
• Exclusion of sequences belonging to aminoacyl-tRNA synthetase (aaRS) clades
• Prioritization of fungal candidates containing putative secretion signals
• Select and analyze a dataset of 300+ candidate sequences.
• Clone and express selected constructs in E. coli or Pichia pastoris.
• Purify enzymes using Ni-NTA affinity chromatography.
• Characterize oligomeric states and solution behavior using size exclusion chromatography.

Expected outcome: Expression, purification, and characterization of >100 enzyme constructs.

2. Kinetic and Mechanistic Characterization

You will perform detailed biochemical and biophysical characterization including:

• Thermostability and ligand binding studies using nanoscale differential scanning fluorimetry (nanoDSF)
• Circular dichroism spectroscopy
• Binding affinity measurements using techniques such as:
• isothermal titration calorimetry (ITC)
• surface plasmon resonance (Biacore)
• fluorescence-based assays
• Kinetic analysis using:
• fluorometric or chromogenic activity assays
• LC–MS based activity measurements

These experiments will determine:

• enzyme specific activity
• optimal temperature and pH
• solvent tolerance
• substrate specificity toward micropollutants

The resulting dataset will form the experimental foundation for machine learning models.

We expect you to have A Master’s degree in biochemistry, biotechnology, bioinformatics, molecular biology, or related fields.

Experience with at least some of the following:

• protein expression and purification
• enzymology or biophysical assays
• bioinformatics or sequence analysis
• structural biology or crystallography
• machine learning or data analysis

Strong programming or data analysis skills (e.g., Python, R) are an advantage.

Excellent communication skills and the ability to work in an interdisciplinary team.

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

Approval and Enrolment

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.

Assessment

The selection process will evaluate candidates through a combination of document review, technical assessment, and interview discussions to ensure they possess the scientific background, analytical thinking, and motivation required for this interdisciplinary project.

Candidates will first be assessed based on their academic transcripts, CV, and previous research experience. Particular attention will be given to coursework and thesis work related to biochemistry, molecular biology, enzymology, bioinformatics, structural biology, or computational biology. Evidence of laboratory experience in protein expression, purification, enzymatic assays, or bioinformatic analysis will be considered a strong advantage.

We offer

DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms

The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

Starting date is according to mutual agreement. The position is a full-time position.

Application procedure

Your complete online application must be submitted no later than 9 April 2026 (23:59 Danish time).

Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

• A letter motivating the application (cover letter)
• Curriculum vitae
• Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale

You may apply prior to obtaining your master's degree but cannot begin before having received it. Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.