********************PostDocs******************** Postdoctoral Position in Evolutionary Genomics and Climate Resilience We are seeking a highly motivated Postdoctoral Researcher to join the GRACE project, investigating evolutionary and genomic responses to climate change in marine species. The successful candidate will lead genomic analyses of natural populations using SNP arrays and low-coverage whole-genome sequencing (lcWGS). They will analyze population structure, genetic diversity, and signatures of selection, and integrate genomic data with experimental phenotypes such as survival, behavior, and condition index. The postdoc will also contribute to the design and analysis of transgenerational plasticity (TGP) experiments and collaborate closely with an interdisciplinary team of scientists within the GRACE consortium. Project context: Climate change, particularly rising temperatures, is rapidly altering ecosystems worldwide, with profound effects on biodiversity. Species living near their thermal tolerance limits are especially vulnerable, leading to shifts in distribution, behavior, and ecological interactions. The GRACE project focuses on two sentinel species the blue mussel (Mytilus edulis) and the copepod (Eurytemora affinis) to understand the genomic and phenotypic mechanisms that underlie thermal resilience. These species are key components of marine and estuarine ecosystems in the Normandy region and serve as excellent models for studying adaptation to climate change. Using a combination of population genomics, controlled heat-stress experiments, and transgenerational assays, the project aims to identify the molecular and phenotypic bases of thermal tolerance and adaptive potential. Essential qualifications: [1] PhD in evolutionary biology, population genetics, genomics, or a related field [2] Strong background in population genomic data analysis (WGS, SNPs, GWAS) [3] Proficiency in R and at least one scripting language (e.g. Python, bash) [4] Solid understanding of evolutionary theory and quantitative genetics Desirable qualifications: [1] Experience with marine or aquatic organisms [2] Familiarity with experimental evolution, transcriptomics, or phenotyping under stress [3] Excellent teamwork and communication skills [4] Publication record in the field Position details: Location: University Le Havre Normandie (ULHN), Le Havre, France Duration: 24 months (minimum) Start date: March 1st, 2026 (flexible) How to apply: Please send a brief statement of research interests, CV, and contact details for two referees to: bastien.saint-leandre@univ-lehavre.fr Additional information: https://umr-sebio.fr Bastien Saint Leandre (to subscribe/unsubscribe the EvolDir send mail to golding@mcmaster.ca) ********************WorkshopsCourses******************** Unlock the Power of Community Ecology Data: Multivariate Analysis of Ecological Communities Using VEGAN https://prstats.org/course/multivariate-analysis-of-ecological-communities-using-vegan-vgnr08/ We have 3 seats left for our upcoming VEGAN course, don't miss, book today! Are you working with species-rich community datasets and seeking the tools to meaningfully analyse, visualise and interpret them? This five-day live online course offers a comprehensive, applied introduction to multivariate techniques in community ecology, using the widely-adopted R package vegan. What the course covers Handling community ecology data: preparing matrices, transforming variables, computing distance measures. Diversity indices, species-abundance distributions and community metrics. Clustering, classification, ordination (unconstrained and constrained), including PCA, NMDS, RDA, CCA. Integrating continuous and categorical predictors to detect ecological patterns along environmental or anthropogenic gradients. Reproducible workflows and best practices in R coding, visualisation and interpretation of results. Why this matters Ecological community data are often high-dimensional, sparse, and structured by environmental gradients or unmeasured factors. The tools you will learn in this course enable you to: Detect underlying structure and patterns in species composition. Quantify relationships between communities and their environment. Present your findings with clarity and rigour. Build workflows that are reproducible, transparent and suited to publication or policy-driven outputs. Who should attend This course is ideal for ecology researchers, conservation scientists, MSc/PhD students, data analysts and environmental practitioners who already have a basic structure in R and want to deepen their analytical toolkit. You should already be comfortable with data import/export, basic manipulation, and fundamental statistical concepts. Format & practicalities Duration: Five full days of live online instruction (~7 hours per day). Participants are encouraged to bring their own datasets; the instructors will help you refine your research questions, select suitable analyses and interpret results. All sessions will be recorded and made available for later review making this suitable for learners across time zones. Fee: 485 (as listed). Take the next step in your analytical journey If you are ready to elevate your community ecology analyses to move beyond univariate summaries and simple graphs into multivariate inference and visualisation this course offers the structured guidance and practical experience you need. -- Oliver Hooker PhD. PR stats Oliver Hooker (to subscribe/unsubscribe the EvolDir send mail to golding@mcmaster.ca)