High-throughput Statistical Modelling of Toxic Effects Assessed By Plant Phenotyping

High-throughput plant phenotyping keeps proving its potential in different areas of crop science and plant breeding and has recently been been suggested as a future means for use in advanced environmental toxicological risk assessment, i.e., as toxicophenomics.  The main aim of environmental risk assessment is to assign magnitudes and probabilities to adverse effects of human impact. A key parameter used in chemical risk assessment is the benchmark dose (BMD), identifying the dose associated with a predefined deviation from non-treated controls in the test system investigated. The BMD methodology relies on non-linear dose-response models and the methodology is well-established for univariate data, such as growth or mortility measured at a single point in time. Dose-response analysis is increasingly being used in omics for large-scale toxicity testing of many markers in one go but the extension to the more complex BMD methodology is lacking.

The primary focus of the PhD project will be on developing the next generation high-throughput BMD methodology for toxicophenomics. Specifically, the aim will be to develop infrastructure for large-scale BMD analysis that may be integrated with tools for pre- and post-processing to achieve a powerful modular toolbox, that can handle different data types and non-standard cases. The data will include phenotyping data in terms of different plant growth parameters, plant physiological measurements and image-based measurements including multispectral and fluorescence measurements. Exploration and validation of the developed methodology to real experimental data is an important aspect of the project.

Who are we looking for?
We are looking for a candidate with strong competences within the field(s) of statistics or bioinformatics. Applicants can have a background in statistics, mathematics, bioinformatics, data science or environmental  toxicology with flair and interest in statistics and data science. The applicant should also be prepared to do some experimental work to produce own data.

Our group and research- and what do we offer?
The successful applicant will be part of the biostatics group at the Department of Plant and Environmental Sciences. We are a part of the crop science section and work closely together with reasearchers across the section and departments on applied statistics within agronomy, eco-toxicology and phenotyping. The crop science section studies and teaches basic and applied sciences related to crop production, with a focus on the interaction between Genotype, Management and Environment. The aim of the crop science section is to improve land management for sustainable food production in a changing climate, by conducting research in laboratories, greenhouses, semi-field and fields. The biostatistics group also works closely together with the environmental toxicology group https://plen.ku.dk/english/research/env_chem_phys/et/  and the analytical chemistry group https://plen.ku.dk/english/research/env_chem_phys/.  These groups focus on the effects of chemical pollutants on individual organisms, populations and ecosystems. Combined, our research projects are closely connected to national and international plant breeders, the agricultural industry, and Danish and European regulatory authorities concerned with the risk assessment of pesticides and industrial chemicals.

The biostatics group is a part of Department of Plant and Environmetal Science, Faculty of SCIENCE, University of Copenhagen. We are located in Taastrup, Copenhagen.

We offer creative and stimulating working conditions in dynamic and international research environment.

Principal supervisor is Associate Professor, Signe M. Jensen, Department of Plant and Environmental Sciences, [email protected], Direct Phone: +4535333431. Co-superviser: Professor, Jan H. Christensen, Department of Plant and Environmental Sciences.

The PhD programme
Qualifications needed for the regular programme
To be eligible for the regular PhD programme, you must have completed a degree programme, equivalent to a Danish master’s degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the project, e.g. statistics, mathematics, environmenal modeling, or environmental toxicology. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database.

Terms of employment in the regular programme
Employment as PhD fellow is full time and for maximum 3 years.

Employment is conditional upon your successful enrolment as a PhD student at the PhD School at the Faculty of SCIENCE, University of Copenhagen. This requires submission and acceptance of an application for the specific project formulated by the applicant.

The terms of employment and salary are in accordance to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State (AC). The position is covered by the Protocol on Job Structure.

Responsibilities and tasks in the PhD program

• Carry through an independent research project under supervision
• Complete PhD courses corresponding to approx. 30 ECTS / ½ FTE
• Participate in active research environments, including a stay at another research institution, preferably abroad
• Teaching and knowledge dissemination activities
• Write scientific papers aimed at high-impact journals
• Write and defend a PhD thesis on the basis of your project

We are looking for the following qualifications:

• Professional qualifications relevant to the PhD project, i.e. qualifications within statistics or bioinformatics and good programming skills.
• Relevant publications within the areas of statistics, modelling or toxicology
• Relevant work experience
• Other relevant professional activities
• Curious mind-set with a strong interest in applied statistics and R programming skills
• Good written and spoken English language skills

Application and Assessment Procedure

Your application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.

Please include:

1. Motivated letter of application (max. one page)
2. Your motivation for applying for the specific PhD project
3. Curriculum vitae including information about your education, experience, language skills and other skills relevant for the position
4. Original diplomas for Bachelor of Science or Master of Science and transcript of records in the original language, including an authorized English translation if issued in another language than English or Danish. If not completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is accepted.
5. Publication list (if possible)
6. Reference letters (if available)

Application deadline:

The deadline for applications is Wednesday 1 March 2023, 23:59 GMT +2.

Interviews with selected candidates are expected to be held in end of March 2023. 

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.