Institute of Biochemistry and Biophysics Polish Academy of Sciences
PhD Student: Procedure no. DSMBBC/2025/21: AI-assisted mapping and biogeographic
Institute of Biochemistry and Biophysics Polish Academy of Sciences, Poland, New York, United States
Institute of Biochemistry and Biophysics Polish Academy of Sciences
Organisation/Company Institute of Biochemistry and Biophysics Polish Academy of Sciences Department Antarctic Biology Department Research Field Biological sciences Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Poland Application Deadline 7 Jan 2026 - 23:59 (Europe/Warsaw) Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Mar 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description PhD project will be carried out within the NCN OPUS 27 grant “Unmanned Aerial Vehicles (UAV) and satellites synergy for monitoring of Antarctic lichen communities (USNEA)”. The research aims to develop and apply advanced remote-sensing approaches and AI-assisted image analysis to investigate the distribution, diversity, and spatial dynamics of Antarctic lichen communities, thereby contributing to biogeographical understanding of polar terrestrial ecosystems.
Lichens constitute the dominant form of vegetation across ice-free Antarctic areas, where harsh environmental conditions limit the presence of vascular plants. Their sensitivity to microclimatic shifts, moisture availability, and deglaciation makes them excellent indicators of ongoing climate-driven environmental change. Yet, large-scale mapping of Antarctic lichens remains challenging due to logistic constraints and the fine spatial heterogeneity of cryptogamic vegetation. Traditional field surveys, although essential, are insufficient for broad-scale monitoring. To address these limitations, the proposed research will integrate UAV-based imaging, satellite remote sensing, and AI-supported classification workflows to quantify lichen distribution at multiple spatial scales.
Field campaigns will be conducted in selected ice-free areas of King George Island, including Rakusa Point, Llano Point, Patelnia Point, and/or Lions Rump and Destruction Bay. These sites encompass a range of microhabitats and environmental gradients characteristic of maritime Antarctica. High-resolution UAV imagery acquired with multispectral, thermal, and hyperspectral sensors will be combined with in-situ validation data, including reflectance measurements and ecological surveys. This dataset will form the foundation for accurate training and validation of image classification models. Complementary satellite imagery (e.g., WorldView-2, WorldView-3 and Pléiades) will enable broader-scale extrapolation and temporal assessment of vegetation dynamics.
The core methodological component of the project is the development of AI-based pipelines for detecting, segmenting, and classifying lichen communities. Convolutional neural networks (e.g., U-Net, DeepLab) and machine-learning algorithms (e.g., Random Forest) will be trained to discriminate among vegetation types and non-vegetated surfaces. These models will integrate UAV and satellite reflectance information, terrain attributes, and field-derived spectral signatures. Analytical workflows will be implemented in Python, R, Matlab and QGIS.
Classification outputs will be integrated with ecological and spatial data to evaluate biogeographical patterns in the distribution of lichens and to identify key environmental drivers of spatial variation. The project embraces an ecoinformatics perspective, combining ecological knowledge with computational and geospatial tools to address fundamental questions in biogeography. Resulting maps and models will be used to characterize patterns of biodiversity, spatial turnover (β-diversity), and habitat associations. Multivariate analyses and spatial modelling (e.g., PCA, RDA, species–environment models) will be used to quantify relationships between lichen assemblages and environmental gradients such as temperature, moisture, wind exposure, snow accumulation, and substrate properties. Temporal analyses will evaluate how vegetation distribution may shift under climate-driven change, such as glacier retreat and increasing ice-free habitats.
Expected outcomes include:
automated classification workflows for identifying lichen assemblages from multi-scale remote-sensing data;
high-resolution vegetation maps of key Antarctic coastal regions;
biogeographical models describing the diversity, spatial structure, and environmental determinants of lichen communities;
improved capability for long-term monitoring of Antarctic Specially Protected Areas (ASPAs).
This PhD project will provide the candidate with training in ecological fieldwork, UAV operations, geospatial data analysis, and advanced computational methods. The interdisciplinary scope aligns with contemporary trends in global change biology and environmental data science. By merging biogeographical analysis with AI-assisted remote sensing, the project will contribute to a deeper understanding of Antarctic terrestrial ecosystems and provide innovative tools for biodiversity monitoring in rapidly changing environments.
Holding a degree of Master of Science [Magister], Master of Engineering [Magister Inżynier], medical doctor or equivalent in the field of: exact sciences, natural sciences, medical sciences or related disciplines, granted by a Polish or foreign university; a person who does not possess the qualifications described above may take part in the competition, but must obtain the qualifications in question and provide the relevant documents before the start of the programme at the Doctoral School (i.e., 1st March 2026).
Languages ENGLISH Level Excellent
Specific Requirements
Solid practical experience with GIS (e.g., QGIS, ArcGIS), including spatial data processing and visualization;
Experience with data analysis using Python, Matlab, and/or R;
Motivation to conduct interdisciplinary research involving remote sensing, ecology, ecoinformatics, and AI-based image analysis;
Strong knowledge in Antarctic and/or polar environmental research;
Readiness and capability to participate in Antarctic fieldwork, including extended stays in remote field stations;
Physical ability to perform fieldwork under demanding conditions (cold temperatures, uneven terrain, prolonged outdoor activity).
Additional Information
Scholarship amount (net, monthly, PLN): 1st year: 4000; 2nd year: 4000; 3rd year: 4932,95; 4th year: 4739,51
Possibility of renting a room in the Institute's hotel for the first 3 months at a special price (depending on rooms’ availability);
Possibility to join a medical plan;
Research mini-grants for doctoral students (up to PLN 20000, a PhD student may apply for funds twice during his/her studies);
Conference Grants (each PhD student can use up to PLN 12,000 to attend conferences during his/her studies);
Surcharge for the multi sport card;
Support in obtaining a temporary residence card (+ Reimbursement of TRC application expenses);
Language courses (Polish, English, German, French, Spanish, Italian… (the offer of courses may change);
Psychological care (up to 5 visits);
Subsidy for the purchase of eyeglasses (once every two years);
Free parking spot.
Selection process The recruitment process consists of two stages:
Selection of candidates by the Committee based on their previous achievements and academic performance presented in the documents submitted; for each position no more than 5 applicants who have achieved the highest scores, but no less than 60% of the maximum points, shall be qualified for the next stage;
An interview conducted by the Committee including in particular: • a presentation delivered by the candidate containing the outcomes of his/her research (a Master’s thesis or other research work carried out by the candidate); the presentation must not last longer than 10 minutes; • questions asked by the members of the Committee related to the presented project, the methods used and interpretation of the results obtained; • questions asked by the members of the Committee related to the proposed PhD programme described in the recruitment announcement; • questions related to the candidate’s motivation for scientific work.
Stage One
learning outcomes (a scale of the evaluation: 0.0 ‒ 6.0 points);
participation in a scientific project or an academic conference (a poster or oral presentation) (a scale of the evaluation: 0.0 ‒ 1.0 points);
co-authorship of a research paper (depending on the role in the publication) (a scale of the evaluation: 0.0 ‒ 1.0 points);
involvement in science club (a scale of the evaluation: 0.0 or 0.5 points);
other achievements, e.g., awards, honors, scholarships, domestic and foreign internships, voluntary work, popularization of science (a scale of the evaluation: 0.0 ‒ 1.5 points).
Stage Two
understanding of the project performed and methods used; the ability to interpret the results obtained; knowledge in the field related to the presented project (a scale of the evaluation: 0-10 points);
knowledge in the field related to the proposed PhD programme described in the recruitment announcement (a scale of the evaluation: 0-10 points);
form of presentation of the candidate’s results (a scale of the evaluation: 0-3 points).
Number of offers available 1 Company/Institute Institute of Biochemistry and Biophysics Polish Academy of Sciences Country Poland State/Province Mazovia City Warsaw Postal Code 02-106 Street ul. Pawińskiego 5a Geofield
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Organisation/Company Institute of Biochemistry and Biophysics Polish Academy of Sciences Department Antarctic Biology Department Research Field Biological sciences Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Poland Application Deadline 7 Jan 2026 - 23:59 (Europe/Warsaw) Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Mar 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description PhD project will be carried out within the NCN OPUS 27 grant “Unmanned Aerial Vehicles (UAV) and satellites synergy for monitoring of Antarctic lichen communities (USNEA)”. The research aims to develop and apply advanced remote-sensing approaches and AI-assisted image analysis to investigate the distribution, diversity, and spatial dynamics of Antarctic lichen communities, thereby contributing to biogeographical understanding of polar terrestrial ecosystems.
Lichens constitute the dominant form of vegetation across ice-free Antarctic areas, where harsh environmental conditions limit the presence of vascular plants. Their sensitivity to microclimatic shifts, moisture availability, and deglaciation makes them excellent indicators of ongoing climate-driven environmental change. Yet, large-scale mapping of Antarctic lichens remains challenging due to logistic constraints and the fine spatial heterogeneity of cryptogamic vegetation. Traditional field surveys, although essential, are insufficient for broad-scale monitoring. To address these limitations, the proposed research will integrate UAV-based imaging, satellite remote sensing, and AI-supported classification workflows to quantify lichen distribution at multiple spatial scales.
Field campaigns will be conducted in selected ice-free areas of King George Island, including Rakusa Point, Llano Point, Patelnia Point, and/or Lions Rump and Destruction Bay. These sites encompass a range of microhabitats and environmental gradients characteristic of maritime Antarctica. High-resolution UAV imagery acquired with multispectral, thermal, and hyperspectral sensors will be combined with in-situ validation data, including reflectance measurements and ecological surveys. This dataset will form the foundation for accurate training and validation of image classification models. Complementary satellite imagery (e.g., WorldView-2, WorldView-3 and Pléiades) will enable broader-scale extrapolation and temporal assessment of vegetation dynamics.
The core methodological component of the project is the development of AI-based pipelines for detecting, segmenting, and classifying lichen communities. Convolutional neural networks (e.g., U-Net, DeepLab) and machine-learning algorithms (e.g., Random Forest) will be trained to discriminate among vegetation types and non-vegetated surfaces. These models will integrate UAV and satellite reflectance information, terrain attributes, and field-derived spectral signatures. Analytical workflows will be implemented in Python, R, Matlab and QGIS.
Classification outputs will be integrated with ecological and spatial data to evaluate biogeographical patterns in the distribution of lichens and to identify key environmental drivers of spatial variation. The project embraces an ecoinformatics perspective, combining ecological knowledge with computational and geospatial tools to address fundamental questions in biogeography. Resulting maps and models will be used to characterize patterns of biodiversity, spatial turnover (β-diversity), and habitat associations. Multivariate analyses and spatial modelling (e.g., PCA, RDA, species–environment models) will be used to quantify relationships between lichen assemblages and environmental gradients such as temperature, moisture, wind exposure, snow accumulation, and substrate properties. Temporal analyses will evaluate how vegetation distribution may shift under climate-driven change, such as glacier retreat and increasing ice-free habitats.
Expected outcomes include:
automated classification workflows for identifying lichen assemblages from multi-scale remote-sensing data;
high-resolution vegetation maps of key Antarctic coastal regions;
biogeographical models describing the diversity, spatial structure, and environmental determinants of lichen communities;
improved capability for long-term monitoring of Antarctic Specially Protected Areas (ASPAs).
This PhD project will provide the candidate with training in ecological fieldwork, UAV operations, geospatial data analysis, and advanced computational methods. The interdisciplinary scope aligns with contemporary trends in global change biology and environmental data science. By merging biogeographical analysis with AI-assisted remote sensing, the project will contribute to a deeper understanding of Antarctic terrestrial ecosystems and provide innovative tools for biodiversity monitoring in rapidly changing environments.
Holding a degree of Master of Science [Magister], Master of Engineering [Magister Inżynier], medical doctor or equivalent in the field of: exact sciences, natural sciences, medical sciences or related disciplines, granted by a Polish or foreign university; a person who does not possess the qualifications described above may take part in the competition, but must obtain the qualifications in question and provide the relevant documents before the start of the programme at the Doctoral School (i.e., 1st March 2026).
Languages ENGLISH Level Excellent
Specific Requirements
Solid practical experience with GIS (e.g., QGIS, ArcGIS), including spatial data processing and visualization;
Experience with data analysis using Python, Matlab, and/or R;
Motivation to conduct interdisciplinary research involving remote sensing, ecology, ecoinformatics, and AI-based image analysis;
Strong knowledge in Antarctic and/or polar environmental research;
Readiness and capability to participate in Antarctic fieldwork, including extended stays in remote field stations;
Physical ability to perform fieldwork under demanding conditions (cold temperatures, uneven terrain, prolonged outdoor activity).
Additional Information
Scholarship amount (net, monthly, PLN): 1st year: 4000; 2nd year: 4000; 3rd year: 4932,95; 4th year: 4739,51
Possibility of renting a room in the Institute's hotel for the first 3 months at a special price (depending on rooms’ availability);
Possibility to join a medical plan;
Research mini-grants for doctoral students (up to PLN 20000, a PhD student may apply for funds twice during his/her studies);
Conference Grants (each PhD student can use up to PLN 12,000 to attend conferences during his/her studies);
Surcharge for the multi sport card;
Support in obtaining a temporary residence card (+ Reimbursement of TRC application expenses);
Language courses (Polish, English, German, French, Spanish, Italian… (the offer of courses may change);
Psychological care (up to 5 visits);
Subsidy for the purchase of eyeglasses (once every two years);
Free parking spot.
Selection process The recruitment process consists of two stages:
Selection of candidates by the Committee based on their previous achievements and academic performance presented in the documents submitted; for each position no more than 5 applicants who have achieved the highest scores, but no less than 60% of the maximum points, shall be qualified for the next stage;
An interview conducted by the Committee including in particular: • a presentation delivered by the candidate containing the outcomes of his/her research (a Master’s thesis or other research work carried out by the candidate); the presentation must not last longer than 10 minutes; • questions asked by the members of the Committee related to the presented project, the methods used and interpretation of the results obtained; • questions asked by the members of the Committee related to the proposed PhD programme described in the recruitment announcement; • questions related to the candidate’s motivation for scientific work.
Stage One
learning outcomes (a scale of the evaluation: 0.0 ‒ 6.0 points);
participation in a scientific project or an academic conference (a poster or oral presentation) (a scale of the evaluation: 0.0 ‒ 1.0 points);
co-authorship of a research paper (depending on the role in the publication) (a scale of the evaluation: 0.0 ‒ 1.0 points);
involvement in science club (a scale of the evaluation: 0.0 or 0.5 points);
other achievements, e.g., awards, honors, scholarships, domestic and foreign internships, voluntary work, popularization of science (a scale of the evaluation: 0.0 ‒ 1.5 points).
Stage Two
understanding of the project performed and methods used; the ability to interpret the results obtained; knowledge in the field related to the presented project (a scale of the evaluation: 0-10 points);
knowledge in the field related to the proposed PhD programme described in the recruitment announcement (a scale of the evaluation: 0-10 points);
form of presentation of the candidate’s results (a scale of the evaluation: 0-3 points).
Number of offers available 1 Company/Institute Institute of Biochemistry and Biophysics Polish Academy of Sciences Country Poland State/Province Mazovia City Warsaw Postal Code 02-106 Street ul. Pawińskiego 5a Geofield
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