Call for a Postdoc Position in Eco-Oncology

We would like to advertise a postdoctoral position for 15 months funded by the Hauts-de-France region within the framework of our project PICCell – Predicting biological Invasion, at the interface between invasive speCies and Cancer cells.

Context and main objectives

Though playing out at very different levels of life organization, cancer cells and invasive alien species (IAS) involve similar processes of invasion, growth and spread. Few recent studies at the frontier between ecology and oncology (i.e., eco-oncology) have made the parallel between both disciplines, calling for interdisciplinary research to better understand the mechanisms that underly invasion success of IAS and cancer cells (e.g. Noorbakhsh et al. 2020, Reynolds et al. 2020, Neinavaie et al., 2021). The PICCell project addresses this challenge by combining the expertise of researchers in both invasion ecology and experimental oncology. PICCell relies on the hypothesis that the “construction” of a new ecological niche is a key step towards the successful invasion for cancer cells and IAS. The bilateral objectives of this interdisciplinary project are: (i) to apply IAS invasion ecology approaches to medical oncology in order to better understanding the mechanisms of tumor invasion and to predict the occurrence and distribution of metastases within target organs; (ii) to use the know-how of medical oncology to better understand the construction of the ecological niche generated by the arrival of an IAS; (iii) to initiate research actions in eco-oncology in order to improve our understanding of invasion success and to decipher the Darwinian and random mechanisms that are key to this success. The tasks proposed to meet these objectives consist in: (1) the application of the niche concept and the so-called species distribution models (SDMs) to cancer cells within the micro-environment of key organs (e.g., the pancreas) to predict the spatial distribution of cancer cells given microenvironmental constraints; and (2) the development of a research consortium.

Main tasks

The successful candidate will apply SDMs’ tools to model the realized niche of human pancreatic cancer cells and identify the micro-environmental variables explaining their distributions (definition of an environmental raster) so as to predict the potential distribution of local (primary tumor) and distant (metastasis) cancer cells. His/her main tasks will be:

  • To ensure an active research survey of academic works and scientific literature at the interface between invasion ecology and experimental oncology;
  • To coordinate the “upstream” steps of the modelling of the realized niche of cancer cells as a function of micro-environmental conditions (e.g., concentration of elements with cells) within cells of the focal organ (i.e., the pancreas);
  • To be in charge of collecting biological, clinical, and “micro-environmental” data from the different partners and contributors involved in PICCell. The candidate will work in close collaboration with a Master 2 student to be recruited to collect and process histopathological data (i.e., cancer cell occurrence data as well as data on micro-environmental conditions in the pancreas) from microscope slides in a “spatialized” and contiguous format, such as raster grids as it is typically used in SDMs in ecology (see below for a more detailed list of tasks);
  • To participate in creating, structuring and moderating the PICCell consortium. The candidate will have a key role in the dialogue between the different partners of the project. She/he will be responsible for identifying and linking their respective skills, thereby anchoring the development of cross-disciplinary issues between ecology and experimental oncology;
  • To implement the following modelling steps, from “tumour” versus “non-tumour” pancreatic histological sections of human and mouse models:
    1. Collect and extract the scenopoetic and bionomic predictive micro-environmental variables obtained from histopathological sections (cf. microscopic slides and pre-processing phase);
    2. Calibrate ecological niche models by correlating the relevant micro-environmental variables with the occurrence and absence of tumour cells in the histological sections;
    3. Project the probabilistic distributions of cancer cell occurrence across independent sets of histological sections for model validation (cf. assessing model interpolation and extrapolation capabilities);
    4. Develop a specific approach to forecast the establishment of metastases in distant organs (i.e., model transferability).
  • To deliver the modelling work carried out in the form of communications and scientific publications with an international audience;
  • To impulse a prospective dynamic by using PICCell as a prism to mobilize other partner teams, new ideas and other sources of funding.


A Ph.D. in numerical ecology, ecoinformatics or a related field. The successful applicant will have:

  • Experience working (or strong interest) on theoretical ecology (familiar with the niche concept);
  • Experience with statistical and modelling tools applied to spatial ecology (e.g., spatial analysis);
  • Good programming skills in the R language or equivalent (Python);
  • Ability to work in a team and interest in interdisciplinarity;
  • Excellent oral and written English language skills;
  • Capacity to work autonomously but also collaboratively.


At the UMR CNRS 7058 « Ecologie et Dynamique des Systèmes Anthropisés » (EDYSAN), 80000 Amiens, France.

Starting date and duration

As early as September 4th 2023 and no later than October 2nd 2023. The postdoctoral position is for 15 months.

Gross salary

To be discussed depending on the experience of the successful candidate.

Application instructions

Applicants must submit a cover letter indicating the date that they will be available to begin the position, a curriculum vitae, copies of 2 publications relevant to the call. Applicants should include names and e-mail addresses for two potential referees.

All application materials must be submitted as PDF(s) in a single email by the closing date, on July 21st 2023, to:

  • Annie Guiller (Prof., PI of PICCell):
  • Jonathan Lenoir (CNRS Researcher):
  • Mathieu Gautier (Prof.) :


  • Service d’Anatomie et de Cytologie Pathologiques, CHU d’Amiens
  • UMR CNRS 7369 MEDyC
  • LPCM UR-UPJV 4667
  • UMR-S 1172

Call for a Postdoc Position in Remote Sensing Applications for Forest Microclimates

Main objective

The EDYSAN lab seeks a postdoctoral candidate for a 13 months period to assess the potential of terrestrial LiDAR to model forest microclimates. The successful candidate is expected to link microclimate data readily available by the lab to stand structure variables derived from terrestrial laser scanning (TLS). Focusing on a subset of sites monitored by the lab, the successful candidate will collect TLS data with a TRIMBLE X7 recently funded by the CPER ECRIN. Several variables will be derived from the 3D LiDAR point cloud, using a voxelization technique, and subsequently used as predictors to model the temporal dynamic of forest microclimates. Several scans throughout the year will be considered to capture the seasonality in the leaf-on and leaf-off periods.

Some background

The position is part of a regional state plan contract under the framework of a large project entitled “Environment, Climate, Research and Innovation” (ECRIN) which aims at identifying and understanding climate change impacts on the atmosphere, human health and ecosystem services to support mitigation and adaptation strategies. The project also aims at supporting the development of innovative measurement methodologies, novel instrumentation to monitor the environment and new advances in analytical approaches. This project involves 29 institutional partners and 25 research laboratories within the Hauts-de-France region.

The EDYSAN lab, who will host the successful candidate, is involved in work package 2 (WP2) entitled “Impacts of climate change on natural, agricultural and suburban systems”. Within the framework of WP2, EDYSAN aims at studying how climate change is impacting the spatial distribution of forest biodiversity and its associated ecosystem services.

Biodiversity redistribution in response to climate change has direct impacts on ecosystem functioning and human well-being throughout the ecosystem services that biodiversity provides. The forest understory is one of the most biodiversity rich compartment in temperate ecosystems worldwide and it harbours a wealth of ecosystem services, such as natural pest control for neighbouring agricultural fields. However, the current tools that are used to predict species distribution and redistribution as climate changes are too coarse in spatial resolution to capture microclimatic processes in the understory and thus unsuitable for forest-dwelling species living under the shade of trees. Not only those models are too coarse in spatial resolution but they are all relying on macroclimatic conditions as measured by standardised weather stations and thus unlikely to capture temperature fluctuations as experienced by forest-dwelling species within their buffered habitats.

In this context, the EDYSAN lab aims at better characterizing and modelling forest microclimates to improve predictions from species distribution models. A recent synthesis published by the lab members in 2022 in Journal of Ecology features how LiDAR technologies, either airborne or terrestrial, can help researchers unveil biodiversity changes through time as well as forest microclimates. An ongoing project funded by the « Agence nationale de la recherche » (ANR, IMPRINT), starting on October 1st 2019 and ending on March 31st 2024, is using this technology to model forest microclimates. This project has already gathered microclimatic data across several sites in several state forests in France (Aigoual, Blois, Compiègne et Mormal), where airborne LiDAR data are readily available, as well as across several permanent forest plots belonging to the « Réseau national de suivi à long terme des écosystèmes forestiers » (RENECOFOR) managed by the « Office national des forêts » (ONF). An equivalent network of permanent forest plots within the Hauts-de-France region is the « Observatoire régional des écosystèmes forestiers » (OREF), managed by the « Centre national de la propriété forestière » (CNPF). Since 2020, 19 permanent forest plots belonging to OREF have been equipped with temperature data loggers (HOBO). Data on forest stand structure and understory plant species composition are also available for all plots.

Main tasks

The main tasks that are expected from the successful candidate are:

  • Acquiring, handling and processing terrestrial LiDAR data from the field;
  • Extracting LiDAR-derived variables (e.g., PAD) using voxel-based approaches;
  • Using LiDAR-derived variables as predictors to model understory temperatures;
  • Writing a scientific article on the benefit of TLS to model forest microclimates.

Expected qualifications

A Ph.D. in remote sensing science, forest sciences or ecoinformatics would be welcome but in general, the candidate we are seeking is expected to have the following skills and qualifications:

  • Remote sensing and experience in using and processing terrestrial LiDAR data;
  • Programming skills, especially in using R and packages such as forestr and lidR;
  • Cutting-edge expertise in modeling and advanced statistical analyses;
  • Basic knowledge in forest ecology and microclimate ecology;
  • Proven abilities to publish at a high international level;
  • Good oral and written communication skills in English;
  • Rigor, curiosity, autonomy, abilities to work in group.


At the UMR CNRS 7058 « Ecologie et Dynamique des Systèmes Anthropisés » (EDYSAN), UFR de Pharmacie, 1 rue des Louvels, 80039 AMIENS Cedex 1, France.

Duration and starting period

The postdoctoral position is for 13 months, with a possibility for a one year extension depending on funding opportunities. The position should start in the beginning of spring 2023 and at the latest on September 2023.

Gross salary

To be discussed depending on the experience of the successful candidate.


A driving licence is required to travel to the study sites located within the Hauts-de-France region.

Application instructions

Please send your CV, including a list of recent publications, together with a cover letter and the contact information of 2 references to Jonathan Lenoir ( and the human resources at UPJV ( The submission deadline is April 30th 2023.