PROJECT NAME
SOIL BIOENGINEERING: ADVANCED METHODS FOR DIAGNOSTICS, MONITORING, AND RESTORATION OF SOIL ECOSYSTEMS
The goal
The project is aimed at establishing the scientific foundations of a new interdisciplinary field – soil bioengineering – which integrates soil science, biogeochemistry, microbiology, nanotechnologies, synchrotron diagnostics, big data analytics, and artificial intelligence. The central idea of the project is to shift from merely documenting soil degradation towards controlled restoration of soil structure, biogeochemical cycles, fertility, and ecological functions through the integration of functional microbiomes and novel nature-like materials.
Project Concept
The project is aimed at establishing the scientific foundations of a new interdisciplinary field – soil bioengineering – which integrates soil science, biogeochemistry, microbiology, nanotechnologies, synchrotron diagnostics, big data analytics, and artificial intelligence. The central idea of the project is to shift from merely documenting soil degradation towards controlled restoration of soil structure, biogeochemical cycles, fertility, and ecological functions through the integration of functional microbiomes and novel nature-like materials.
Key Scientific Hypothesis
Sustainable recovery of a soil ecosystem can be achieved not through a single intervention targeting a pollutant or an individual soil component, but through the deliberate engineering of the "soil–material–microbiome–plant" system. Combining molecular-level diagnostics with the analysis of biogeochemical and biological responses will enable the selection of the optimal remediation technology for a specific soil type, contamination nature, and degradation degree.
Scientific Novelty
The novelty of the project lies in the integration of high-resolution physicochemical diagnostics and biological restoration technologies into a single manageable system. In contrast to traditional approaches that primarily assess the reduction of gross contaminant content, this project focuses on the mechanisms of contaminant transformation and bioavailability, as well as on the restoration of microbiological processes, rhizosphere interactions, and ecological functions of soils. Artificial intelligence is viewed not as an end in itself, but as a tool for integrating heterogeneous experimental data and selecting the optimal remediation strategy.
Project Tasks
- To develop a multi-level system for soil diagnostics across the scale: "atom–molecular level – particle – rhizosphere – soil profile – ecosystem".
- To identify and assemble functional microbial consortia capable of biodegrading organic pollutants, transforming potentially toxic elements, and restoring biogeochemical soil functions.
- To investigate the transformation, migration, bioavailability, and binding mechanisms of heavy metals, metalloids, and organic contaminants (including PAHs) in the "soil–plant–microorganism" system.
- To develop multifunctional remediation systems based on biochar, layered double hydroxides, and other promising organo-mineral and nanostructured materials, including their combinations with functional microbiota.
- To employ XANES/EXAFS, X-ray microfluorescence, electron microscopy, chromatographic, and mass-spectrometric methods to elucidate the mechanisms of contaminant interaction with the soil matrix and remediation materials.
- To develop principles of multi-stage remediation for soils with combined stress factors, including contamination with heavy metals and PAHs, salinization, and reduced biological activity.
- To generate comprehensive experimental datasets on soil properties, contaminants, materials, microbiomes, and plant responses, and to apply machine learning techniques to reveal hidden relationships and predict remediation efficiency.
- To create a prototype of an intelligent decision support system for selecting soil restoration technologies, taking into account soil type, the nature and level of anthropogenic impact, remediation agent properties, and target ecological functions.
Research Methods
Synchrotron and X-ray spectroscopic methods: XANES, EXAFS, XRF, and micro-XRF for speciation analysis and determination of local atomic environment.
Chromatographic and mass-spectrometric methods for the determination of PAHs and other organic contaminants.
Atomic absorption spectrometry, elemental analysis, FT-IR spectroscopy, NMR, X-ray diffraction analysis, and specific surface area and porosity analysis.
Scanning and transmission electron microscopy for the study of material morphology, microorganisms, and plant tissues.
Soil chemistry and biogeochemistry methods, including metal fractionation, assessment of buffer capacity, mobility, and bioavailability of contaminants.
Microbiological and molecular biological methods for functional microbiome characterization and selection of promising microbial consortia.
Physiological and biochemical plant assessment techniques, including growth parameters, stress response, and photosynthetic activity.
Statistical analysis, multivariate data processing, and machine learning methods for soil condition classification, identification of predictors of remediation efficiency, and construction of predictive models.
Expected Results
- A scientifically grounded concept of bioengineering for degraded and contaminated soils.
- New data on the molecular mechanisms of interaction between heavy metals and organic contaminants with the soil matrix, plants, microorganisms, and remediation materials.
- Functional microbial consortia and biocomposite systems for the restoration of contaminated soils.
- Multifunctional materials and combined remediation technologies based on biochar, layered double hydroxides, and microorganisms.
- A comprehensive interconnected experimental dataset covering "soil–contaminant–material–microbiome–plant".
- Machine learning-based predictive models for risk assessment and evaluation of soil restoration efficiency.
- A prototype of an intelligent platform for selecting remediation technologies and restoring soil ecological functions.
- Publications in high-impact international journals, preparation of intellectual property, participation in international conferences, and training of early-career researchers.
Principal Researcher
- Tatyana MinkinaDoctor of Biological Sciences, Professor, Head of the Department of Soil Science and Land Resources Assessment, Southern Federal University; Head of the Strategic Project "Soil Bioengineering" at Southern Federal University under the "Priority 2030" Program.
Research areas: soil chemistry, geochemistry and biogeochemistry, monitoring, diagnostics, and restoration of contaminated soil ecosystems.
Personal page
Scopus Author ID: 15063165400
ResearcherID Web of Science: A-1683-2014
ORCID ID: http://orcid.org/0000-0003-3022-0883
SPIN-код: 3863-6522, AuthorID: 63033
Postdoc
- Role of the Postdoctoral FellowThe postdoctoral fellow will be integrated into an interdisciplinary team and will have the opportunity to develop their own research direction within the framework of the project. The work will include: designing and conducting experiments, data processing and interpretation, preparation of publications and intellectual property, participation in international research, supervision of graduate and postgraduate students, and development of a youth research group.
- Candidate Requirements
- PhD or equivalent academic degree relevant to the project profile.
- Research experience in one or more of the following fields: soil science, environmental sciences, biogeochemistry, microbiology, biotechnology, analytical chemistry, nanomaterials.
- Publications in journals indexed in Scopus and/or Web of Science.
- Experience in experimental work and scientific data interpretation.
- Experience with chromatography, mass spectrometry, atomic absorption spectrometry, electron microscopy, X-ray spectroscopic or synchrotron methods is an advantage.
- Proficiency in statistical analysis, Python/R, and machine learning methods is an advantage.
- Ability to work in an international interdisciplinary team and to prepare scientific publications in English.
Soil Science; Environmental Sciences; Biogeochemistry; Environmental and Applied Microbiology; Biotechnology; Plant Sciences; Nanomaterials and Nanotechnologies; Synchrotron Research; Data Analytics and Artificial Intelligence.
Academy of Biology and Medicine named after D.I. Ivanovsky of the Southern Federal University, utilizing the infrastructure of youth research laboratories and research centers of SFedU, as well as synchrotron facilities through scientific collaborations.
- Terms and ConditionsThe salary starts from 130,000 RUB per month and may be higher depending on qualifications and assigned tasks.
Organizational support will be provided for visa and accommodation matters, as well as support for academic mobility and integration of the researcher into the scientific environment of Southern Federal University.
The expected duration of the position is up to 3 years
Working Languages