********************PostDocs******************** The Professorship of Forest Genetics seeks to hire a *Postdoctoral Researcher (m/w/d)* * Application deadline: March, 10th 2026 * Starting data: as soon as possible * Fulltime position Our research team for Forest Genetics at the Albert-Ludwigs-Universität Freiburg investigates the genomic and epigenetic basis of adaptation and acclimation in temperate and tropical tree species. Our research is carried out in natural populations as well as in greenhouses and climate chambers, and we have experience collecting and analyzing genetic, genomic, phenotypic, and environmental data. We value collaborative, open, and respectful communication within our diverse and international team. For our team, we are seeking a postdoctoral researcher with experience analyzing genomic datasets in non-model species and the motivation to work in tree genetics for the next 4-6 years. The postdoctoral researcher will have the opportunity to establish his/her own profile in forest genetics research and teaching and will be integrated into some of our ongoing research projects (https://uni-freiburg.de/enr-forgen/). After a training phase, you will also support the working group with data management on DataPlant (https://www.nfdi4plants.org/). The position has a teaching obligation of four semester hours per week. This includes a course on bioinformatic analysis of genetic datasets for MSc students, which should be coordinated and taught independently. Contributions to a course on forest genetics lab and data analysis skills for MSc students and a lab practical course for BSc students are also expected. *Your profile* * You hold a very good Master's degree in biology, forest sciences, bioinformatics, or related fields, and have completed a Ph.D. in forest genetics or a closely related area. * You have experience in analyzing genomic data, especially RNAseq and whole-genome sequencing datasets. * You are experienced in lab work (e.g., DNA/RNA extractions) and ideally in running and analyzing qPCRs. * You are proficient in bioinformatic analyses (including HPCs), comfortable in Unix environments, and experienced with R; Python knowledge and willingness to learn new analysis pipelines are a plus. * Ideally, you are familiar with the challenges of working with non-model species. * You can carry out scientific work independently, as demonstrated by your publications. * You thrive in teamwork, collaborate effectively in diverse and international groups, and communicate openly and respectfully with colleagues. * You have experience teaching and supervising BSc and MSc theses, with good to very good teaching evaluations. MSc-level lectures and group communication are in English, so excellent English skills are required; good German skills are an advantage for administrative and BSc-level teaching tasks. *What we offer* You will be integrated into our working group at the University of Freiburg. We are broadly interested in the adaptation and acclimation processes of trees, and in the genetic diversity and gene flow in tree populations in temperate and tropical regions. With several recently started large collaborative projects, including the Cluster of Excellence "Future Forests," the University of Freiburg is becoming a hub for forest science with many opportunities for national and international collaborations. The position offers the possibility of scientific qualification. The postdoctoral researcher will be supported in writing his/her own research proposals. The salary follows the standard postdoctoral scale in Germany, including social security and health insurance. *Your application* Your application should include a letter of motivation, an academic CV (including an overview of your research and teaching activities, an overview of data analysis and software skills, and a publication record), copies of academic transcripts, and contact details for two academic references. Please upload the applicants as a single document to the application portal of the University of Freiburg (https://uni-freiburg.de/stellenangebot/00004860). Prof. Dr. Katrin Heer Forest Genetics Eva Mayr-Stihl Stiftungsprofessur für Forstgenetik Albert-Ludwigs-Universität Freiburg Fakultät für Umwelt und Natürliche Ressourcen Bertoldstraße 17, 79098 Freiburg i. Br., Germany Phone: +49 761 203 3647 www.forestgenetics.uni-freiburg.de Katrin Heer (to subscribe/unsubscribe the EvolDir send mail to golding@mcmaster.ca) ********************PostDocs******************** The call for the prestigious "Eawag-Postdoc", a 2-year postdoctoral fellowship at Eawag, the Swiss Federal Institute of Aquatic Science and Technology, is open: https://apply.refline.ch/673277/1335/pub/2/index.html The deadline for applications is 5 April 2026. Please refer to the advert for details. The call is open for researchers in any field within the area of aquatic sciences, and we strongly encourage ecologist and evolutionary biologists to apply. Information on Eawag's research departments can be found here: https://www.eawag.ch/en/about-us/portrait/organisation/research-departments/ Interested candidates have the opportunity to define their own research project at Eawag. The followship includes research support. Feel free to contact any of Eawag's research group leaders to discuss possibilities. *** Christoph Vorburger Eawag, Swiss Federal Institute of Aquatic Science and Technology & Institute of Integrative Biology, ETH Z�rich �berlandstrasse 133 8600 D�bendorf Switzerland Phone: +41 58 765 5196 e-mail: christoph.vorburger@eawag.ch or vorburgc@ethz.ch group homepage: http://homepages.eawag.ch/~vorburch/ *** "Vorburger, Christoph" (to subscribe/unsubscribe the EvolDir send mail to golding@mcmaster.ca) ********************PostDocs******************** Post-doc position A newly established lab at the Institute of Evolutionary Biology, University of Warsaw, invites applications for a postdoctoral-level Assistant Professor position funded by the Polish National Science Centre (SONATA project). The project "How changes in meristem patterning drive evolutionary innovations: insights from syncephalia in the sunflower family (Asteraceae)" investigates the developmental and genomic basis of morphological innovation in plants using comparative genomics, developmental transcriptomics, and gene expression analyses. We seek candidates with experience in plant evolutionary developmental biology (e.g. in situ hybridization, regeneration/transformation approaches) or comparative genomics/transcriptomics in evolutionary research. The position is full-time, starting October 2026 (initial 12-month contract with possible extension). Application deadline: 30 April 2026 For more details, visit: https://www.biol.uw.edu.pl/wp-content/uploads/sites/19/2026/02/ogloszenie-WB-KG-1-2026-EN.pdf ___ Doctoral position A newly established lab at the Institute of Evolutionary Biology, Faculty of Biology, University of Warsaw invites applications for a PhD student position funded by the Polish National Science Centre (NCN, SONATA-20 project). Project desciption: The sunflower family (Asteraceae), with more than 32,000 species, owes much of its evolutionary success to the capitulum, a complex, flower-like inflorescence that has undergone repeated modifications. One such innovation is syncephaly, in which capitula are composed of smaller, often highly reduced capitula. The project aims to uncover the evolutionary-developmental mechanisms underlying the formation of these fractal-like blossoms. The PhD project will integrate: - comparative genomics - transcriptomics - in situ gene expression analyses - functional and developmental approaches The successful candidate will conduct research within the project, prepare scientific publications, and present results at national and international conferences. Position details - Number of positions: 1 - Project duration: 36 months - Expected start: October 2026 - Monthly scholarship: ~3700 PLN net/month (years 1-2), increasing to ~4900 PLN net/month after midterm evaluation - Possibility to additionally apply for funding through the University of Warsaw Doctoral School Candidate requirements - MSc degree in biology, biotechnology, environmental science, or a related discipline - Basic background in plant biology - Either: laboratory experience (e.g. DNA/RNA isolation, PCR, electrophoresis), or computational experience (Unix environment, R and/or Python) - Good command of English (spoken and written) Application materials - Academic CV including research experience and skills - Copy of MSc diploma - One recommendation letter from a previous supervisor Applications should be sent directly to: j.baczynski@uw.edu.pl Selected candidates will be invited for short online interviews in the second half of April 2026. Application deadline: 17 April 2026 Expected decision date: 1 May 2026 Jakub Baczyñski, PhD Institute of Evolutionary Biology, Faculty of Biology, Biological and Chemical Research Centre, University of Warsaw ul.¯wirki i Wigury 101, 02-089 Warsaw, Poland e-mail:j.baczynski@uw.edu.pl website:ibe.biol.uw.edu.pl Jakub Baczyñski (to subscribe/unsubscribe the EvolDir send mail to golding@mcmaster.ca) ********************WorkshopsCourses******************** Dear evoldir members, Transmitting Science is offering the course "Proteomic Methods for Species Identification of Archaeological and Palaeontological Materials" (3rd edition). Learn more and register here: https://www.transmittingscience.com/courses/genetics-and-genomics/palaeoproteomics-and-zooarchaeology-by-mass-spectrometry-zooms/ In this course, participants will be introduced to proteomic methods for species identification, focusing on peptide mass fingerprinting by MALDI-ToF mass spectrometry and LC-MS/MS based approaches. During the course, participants will first be introduced to some theory with illustrative examples (both from simulated data as well as some real datasets) and will then learn how to interpret the data, both MS1 (e.g., fingerprints) and MS2 (or MS/MS 'sequencing' spectra), as well as how to assess their reliability. Instructor: Dr. Michael Buckley (University of Manchester, UK), author of ZooMS (Zooarchaeology by Mass Spectrometry) If you have any questions do not hesitate to contact us at courses@transmittingscience.com Best regards, Haris Haris Saslis, PhD Course Coordinator Transmitting Science www.transmittingscience.com [1] Links: [1] http://www.transmittingscience.com Haris Saslis - Transmitting Science (to subscribe/unsubscribe the EvolDir send mail to golding@mcmaster.ca) ********************WorkshopsCourses******************** Introduction to Processing and Analysis of Spatial Multiplexed Proteomics Data (SPMP02) https://www.prstats.org/course/introduction-to-processing-and-analysis-of-spatial-multiplexed-proteomics-data-spmp02/ Dates:1-5 June 2026 Format:Live online, 5 days × 5.5 hours per day Fee:450 Time zone:UK (GMT+1); all sessions are recorded and made available for 30 days Why This Course Matters Spatial multiplexed proteomics techniques such as CODEX, CycIF, and MxIF/MACSIMA are revolutionising how we understand tissue microenvironments, cellular interactions, and spatial heterogeneity in biological systems. However, converting raw multiplexed imaging data into actionable biological insight requires expertise in image processing, spatial statistics, phenotyping, and bioinformatics pipelines. SPMP01bridges that gap. Over five intensive days, you will learn both the theoretical foundations and the hands-on computational skills needed to process, analyse, and interpret spatial multiplexed proteomics data. Whether your work lies in basic biology, cancer immunology, neuroscience, or spatial systems biology, this course equips you to handle complex image-based proteomics datasets. What You'll Learn Participants will move from foundational concepts to applied workflows across these core topics: Overview and comparison of spatial multiplexed imaging platforms (CODEX, CycIF, MxIF / MACSIMA) Image processing workflows: tile stitching, illumination correction, alignment, and region-of-interest generation Handling multi-resolution image formats (e.g., .tif, .ome.tif, .ome.zarr), and visualization strategies Single-cell segmentation: algorithms (e.g. Cellpose, Stardist, Mesmer), mask QC, and error diagnostics Feature extraction and cell phenotyping (marker intensity gating, clustering, annotation) Spatial neighbourhood and cell-cell interaction analysis: quantifying local and global neighbourhood statistics Batch processing and scalable workflows (using Nextflow pipelines such as MCMICRO) Best practices for reproducibility, data storage, workflow modularity, and integration with R/Python pipelines Through guided coding sessions and worked examples, you will apply these methods to real multiplexed imaging datasets and gain experience interpreting spatial proteomics results. Format & Support Each day blends lectures, demonstrations, and hands-on practical work Participants are encouraged to bring their own data for discussion (time permitting) All course materials, scripts, and datasets are shared with attendees Livestream sessions are recorded and made available the same day Post-course email support is offered for 30 days to assist with implementation and troubleshooting Who Should Attend This course is aimed at researchers, computational biologists, bioinformaticians, and technical scientists who work with or plan to work with spatial omics and proteomics imaging data. Prior experience with R or Python is advantageous. Basic knowledge of statistics and familiarity with image data (microscopy) will help, but are not strict prerequisites. A comfortable level of computing literacy (e.g. command line use) is expected. Instructors Dr Victor Perez Meza an expert in fluorescence microscopy, image artefact correction, and multiplexed imaging workflows MSc Miguel Angel Ibarra Arellano specialist in reproducible bioimage analysis, neighbourhood spatial statistics, and spatial omics tools Their combined experience ensures a mix of methodological insight and practical, cutting-edge implementation. Who Will Benefit (Use Cases) Participants in SPMP01 will be better equipped to: Process and clean raw multiplexed imaging datasets Segment individual cells reliably and assess segmentation quality Assign cell phenotypes and derive per-cell morphological or marker statistics Quantify spatial relationships and neighbourhood structure in tissue Develop reproducible pipelines for spatial proteomics workflows Integrate processed spatial data into downstream statistical or machine learning analyses In fields such as cancer microenvironment analysis, immunology, neuroscience, and developmental biology, these capabilities are invaluable for linking cellular spatial patterns to functional and phenotypic insights. Registration & Details Spaces are limited to ensure a high-quality interactive experience. The early bird rate (400) is available to the first five registrants. Standard registration is 450. Visit the course page for full schedule, registration, and further details: SPMP02 - Introduction to Processing and Analysis of Spatial Multiplexed Proteomics Data Email oliver@prstats.org with any questions Oliver Hooker PhD. PR stats Oliver Hooker (to subscribe/unsubscribe the EvolDir send mail to golding@mcmaster.ca)