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We have an open position for an incoming postdoctoral research fellow position within computational narrative systems.

The applicant must propose an individual project in computational narrative systems that will be the focus of the postdoctoral work. The Center for Digital Narrative’s Computational Narrative Systems node, led by @nickmofo studies and researches the computational modeling of narrative, which includes developing new computational models of narrative and re-implementing historical models (also known as “storytelling systems”) so that they can be easily studied and used.

jobbnorge.no/en/available-jobs #researchjobs

Jobbnorge.noLead AI Postdoctoral Research Fellow Position within Digital Narrative (277025) | University of BergenJob title: Lead AI Postdoctoral Research Fellow Position within Digital Narrative (277025), Employer: University of Bergen, Deadline: Sunday, May 11, 2025
INRAE JobsIngénieur-e biologiste en imagerieIR25-ECODIV-2 - Vous intégrerez l'Unité mixte de recherche (UMR) SILVA (INRAE, AgroParisTech, Université de Lorraine). L'unité a pour objectif de développer des travaux pluridisciplinaires sur l'adaptation des écosystèmes forestiers aux changements globaux. Intégrée à SILVA, la plateforme technologique SILVATECH labellisée par INRAE propose des services d'analyses, de développement et de formation à partir d'une gamme d'équipements de haute technologie regroupés dans deux pôles : Isotopie-Chimie (IC) et Imagerie et Mesures Multi-Modales (I3M) que vous intégrerez pour y assurer les missions suivantes :- En collaboration avec les communautés de recherches locales, nationales et européennes, vous mettrez à profit vos connaissances et vos compétences initiales fortes en biologie et physiologie végétale aux échelles fines, pour mieux appréhender et caractériser par imagerie, les réponses physiologiques et anatomiques de l'arbre aux contraintes de son environnement. Dans le cadre du projet de recherche de l'unité SILVA, vous conduirez des travaux permettant d'identifier des marqueurs anatomiques et physiologiques de la tolérance ou de la vulnérabilité de l'arbre aux stress multiples (ex : sécheresse, ennoyage, vent, attaque biotique). Pour ce faire, vous serez chargé-e de développer des méthodologies de microscopie corrélative permettant de combiner les informations biologiques acquises, à partir de différents équipements, sur les mêmes échantillons par des approches multi-échelles et multi-techniques. Ces approches corrélatives permettront de créer des passerelles entre les échelles micro à nanométriques mais aussi de combiner des informations structurales et fonctionnelles voire dynamiques à partir des échantillons observés. Pour ce faire, vous développerez des itinéraires méthodologiques complets et intégrés à partir du large éventail d'équipements récents présents sur le pôle I3M (2 Cryo-MEB équipés en micro-analyse EDS, WDS et RX, un microscope confocal à balayage laser, un microscope à microdissection laser, une station d'imagerie photonique numérique, un multiscanner RX, un système d'imagerie hyperspectrale, divers équipements reposant sur l'utilisation des rayons X ainsi que des équipements de préparations en microscopie, un plateau de préparation en histologie) et dynamiserez les liens entre les approches présentes sur le pôle (densité stomatique, densité des vaisseaux du bois, anatomie quantitative à grande échelle, dendrométrie/chronologie/chimie). - Vous coanimerez le pôle I3M constitué de neuf agents, en assurant des activités telles que la gestion des plannings et activités des agents, le développement et la validation de méthodes, le contrôle et gestion de la maintenance, l'investissement significatif dans la prévision, l'élaboration et la conduite des dossiers stratégiques (achat d'équipement, expertise), l'apport d'expertise au montage de projets et l'application des démarches qualités. Pour mener à bien cette mission, vous travaillerez en relation étroite avec les autres animateurs de pôle et le responsable de la plateforme Silvatech.- Vous coordonnerez une partie du parc d'équipements associé au pôle I3M en collaboration avec leurs responsables techniques.- Vous assurez et/ou coordonnerez la formation de stagiaires/doctorants/post-doc aux techniques et équipements de microscopie dans un cadre local ou national.- Vous vous impliquerez fortement dans les réseaux technologiques (ex : RCCM-RIME, COST COMULIS) afin d'assurer la veille technologique et la valorisation de vos travaux de développement dans ces communautés. Cette valorisation passera également par la rédaction et la participation active à des publications scientifiques aussi bien en biologie qu'en techniques instrumentales.

📣 We are #hiring!

We are looking for a GIScience researcher for a Postdoctoral Fellowship (6-12 months) on Climate Action, Open Geodata & VGI.

Are you a researcher with a passion for spatial data science and open geodata? Do you want to use your expertise about GHG emission inventories or active mobility to develop spatial indicators for Climate Action?

We look forward to receiving your application: heigit.org/job-posting/heigit-

Awesome looking job alert!!

I'd almost give a kidney to be based in Canmore and do this work. Unfortunately visa alignment is no good and family is well, rightly afraid of a Norway repeat - so if you have working rights in Canada:

usask.csod.com/ux/ats/careersi

usask.csod.comResearch Technician (UAV Specialist)Primary Purpose: The Centre for Hydrology at the University of Saskatchewan is seeking a Research Technician (Unoccupied Aerial Vehicle (UAV) speciali...

The French National Agronomy Research Institute #INRAE has a #JobOpportunity for a #Trees #BioMechanics (or #MechanoBiology ) researcher (permanent position). Even though the description is in the moment only in French, international applications are welcome :
jobs.inrae.fr/concours/concour
#SciJobs #Vacancy #JobOpening #ResearchJobs #academia #Forests #Wood
@academicchatter

INRAE JobsChargé-e de recherche en biomécanique de l'arbreCR-2025-ECODIV-1 - L'UMR SILVA (Université de Lorraine, AgroParisTech, INRAE) est une unité pluridisciplinaire d'environ 150 agents. Elle étudie le fonctionnement des écosystèmes forestiers dans le contexte des changements globaux avec un focus particulier sur les risques multiples liés à des combinaisons de différents aléas (vent, sécheresse, engorgement), pour proposer des solutions de gestion et d'adaptation. Vous développerez un projet de recherche dont l'objectif est d'intégrer le signal biomécanique reçu par les arbres dans les modèles de dynamique forestière.L'allocation de croissance au sein de l'arbre s'avère fortement régulée par ces signaux avec des conséquences importantes sur les dynamiques forestières. La perception du signal mécanique par les cellules vivantes est un facteur très connu des biologistes mais méconnu en forêt, et pourtant essentiel du contrôle environnemental de la croissance des arbres et de la rétroaction active dans un contexte d'acclimatation ou de réponse aux risques. La réponse à ce signal façonne la forme des arbres et par conséquent leurs traits d'acquisition des ressources, de résistance ou de résilience aux différentes contraintes. Elle conditionne donc les services rendus par les écosystèmes forestiers, dont le stockage de carbone, souterrain ou aérien. L'intégration de la réponse au signal biomécanique dans les modèles de dynamique forestière est un enjeu important pour accéder à des prédictions réalistes pour des forêts soumises à des risques multiples et aux facteurs multiples de régulation de la croissance.Vous développerez un cadre conceptuel en émergence dans les communautés internationales, combinant l'approche mécanique du risque vent sur une structure arborée et la mécanobiologie de la croissance. Pour cela, vous formaliserez l'intégration de mécanismes physiologiques et écophysiologiques dans le calcul des performances mécaniques des arbres (résistance au vent, capacité de redressement, autoportance) ainsi que pour la prédiction des trajectoires temporelles de celles-ci à l'échelle du peuplement forestier dans le contexte des changements globaux. Vous mobiliserez connaissances et approches de la mécanique des matériaux et des structures mais aussi de la biologie des arbres forestiers.Vous confronterez ce cadre aux problématiques d'évaluation des risques auxquels sont soumis les peuplements forestiers, traitées dans l'UMR Silva. Vous pourrez vous appuyer sur les compétences en métrologie et en modélisation de la croissance de vos collègues de l'unité, sur l'accès aux dispositifs de suivi de peuplements forestiers gérés par l'UMR Silva, sur les infrastructures nationales d'expérimentation et d'observation en forêt (In Sylva France, AnaEE et ICOS) ainsi que sur la plate-forme analytique Silvatech pour la caractérisation des propriétés anatomiques et mécaniques du bois et la plateforme de modélisation CAPSIS.

Join FCAI for your #PhD or #postdoc! There are over 30 supervisors to choose from in the following research areas:

1) Reinforcement learning
2) Probabilistic methods
3) Simulation-based inference
4) Privacy-preserving #machinelearning
5) Collaborative AI and human modeling
6) Machine learning for #science

Positions are at the University of Helsinki or Aalto University.
Apply by Feb. 2: fcai.fi/winter-2025-researcher

We’re hiring researchers to help drive impactful work!🌟
If you’re passionate about media engagement and research, we’d love to hear from you.

Check out our open positions here:
🔗 utaustin.wd1.myworkdayjobs.com
🔗 utaustin.wd1.myworkdayjobs.com

utaustin.wd1.myworkdayjobs.comCME Humanities Research Associate VJob Posting Title: CME Humanities Research Associate V ---- Hiring Department: Media Engagement, Center for ---- Position Open To: All Applicants ---- Weekly Scheduled Hours: 40 ---- FLSA Status: Exempt ---- Earliest Start Date: Immediately ---- Position Duration: Expected to Continue Until Nov 30, 2025 ---- Location: UT MAIN CAMPUS ---- Job Details: Purpose This role is eligible for hybrid or fully remote work. The Research Engineer will support the Center for Media Engagement's research on connective democracy. Responsibilities Maintain a data lake system with archives of static and streaming internet and news data that can be queried by researchers. Seek out, scrape and support new datasets that are of interest to CME faculty. Manage the security of the archive, including access, encryption, and security training. Regularly review security measures, permissions, and encryption protocol. Manage data back-ups. Store and update documentation of datasets, including provenance files/data sheets, access protocols, and security measures. This may involve some software development. Develop, implement, and evaluate supervised and unsupervised classifiers, including training and testing classifiers (e.g., BERT, GPT, CNN) for multiple research projects. Recommend and execute strategies to improve model performance and efficiency. Document the process and contribute to research and open-source initiatives, including writing model cards. Work with and support researchers with various backgrounds in computational methods to inform their research designs. Follow emerging trends in computational research (e.g. RAG, RLHF) and use these learnings to inform researchers of how they could apply to their work. Other duties as assigned. Required Qualifications Masters degree in computer science or information with six years of relevant experience. Technical Skillset: Python (pandas, numpy), R, SQL/Hadoop, Tensorflow/Keras/Huggingface, Github, unix/cmd, github, AWS/Azure/GCP Significant knowledge in machine learning and working with large data Ability to develop and optimize data science software Management of data infrastructure Experience working with multiple project and collaborating with teams Clear and timely communication Relevant education and experience may be substituted as appropriate. Preferred Qualifications Experience using Rest APIs and/or data scraping Knowledge of or experience with signal processing, computer vision, or network analysis Experience with open-source software/OSINT An ideal candidate should have experience with “big” data and cloud computing/infrastructure. Salary Range $80,000 + depending on qualifications Working Conditions Typical office environment Required Materials Resume/CV 3 work references with their contact information; at least one reference should be from a supervisor Letter of interest Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded. Once your job application has been submitted, you cannot make changes. Important for Current university employees and contingent workers: As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume. In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above. ---- Employment Eligibility: Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval. ---- Retirement Plan Eligibility: The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. ---- Background Checks: A criminal history background check will be required for finalist(s) under consideration for this position. ---- Equal Opportunity Employer: The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions. ---- Pay Transparency: The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. ---- Employment Eligibility Verification: If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university. ---- E-Verify: The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university’s company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following: E-Verify Poster (English) [PDF] E-Verify Poster (Spanish) [PDF] Right To Work Poster (English) [PDF] Right To Work Poster (Spanish) [PDF] ---- Compliance: Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031. The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701. In 2024, The University of Texas at Austin was recognized as a 5 Year Champion having placed in the top 10 among Texas employers and top 15 for higher education institutions on Forbes’s list of 500 best large employers five years running. The University’s aspiration to become the world’s highest-impact public research university is driven by our outstanding people. Our employees are the bedrock of our university and are empowered to be true to themselves, to participate fully in our vibrant university, and to thrive as individuals. UT Austin offers competitive salaries, full benefits, an extensive support network, and above all, an enriching and highly collaborative working community that is deeply passionate about our vision for higher education and public service. Looking for a student job? Please see our Student Employment site. Comments and Inquiries: Email comments to: Human Resource Service Center. For questions or concerns regarding equal opportunity only, contact Equal Opportunity Services. Additional information for applicants can be found on the Human Resources web page: Applying for Employment. For more job information, call the Human Resource Service Center at (512) 471-4772, or toll-free at (800) 687-4178. UT Austin is a Tobacco-free Campus

We’re hiring researchers to help drive impactful work!🌟
If you’re passionate about media engagement and research, we’d love to hear from you.

Check out our open positions here:
🔗 utaustin.wd1.myworkdayjobs.com
🔗 utaustin.wd1.myworkdayjobs.com

utaustin.wd1.myworkdayjobs.comCME Humanities Research Associate VJob Posting Title: CME Humanities Research Associate V ---- Hiring Department: Media Engagement, Center for ---- Position Open To: All Applicants ---- Weekly Scheduled Hours: 40 ---- FLSA Status: Exempt ---- Earliest Start Date: Immediately ---- Position Duration: Expected to Continue Until Nov 30, 2025 ---- Location: UT MAIN CAMPUS ---- Job Details: Purpose This role is eligible for hybrid or fully remote work. The Research Engineer will support the Center for Media Engagement's research on connective democracy. Responsibilities Maintain a data lake system with archives of static and streaming internet and news data that can be queried by researchers. Seek out, scrape and support new datasets that are of interest to CME faculty. Manage the security of the archive, including access, encryption, and security training. Regularly review security measures, permissions, and encryption protocol. Manage data back-ups. Store and update documentation of datasets, including provenance files/data sheets, access protocols, and security measures. This may involve some software development. Develop, implement, and evaluate supervised and unsupervised classifiers, including training and testing classifiers (e.g., BERT, GPT, CNN) for multiple research projects. Recommend and execute strategies to improve model performance and efficiency. Document the process and contribute to research and open-source initiatives, including writing model cards. Work with and support researchers with various backgrounds in computational methods to inform their research designs. Follow emerging trends in computational research (e.g. RAG, RLHF) and use these learnings to inform researchers of how they could apply to their work. Other duties as assigned. Required Qualifications Masters degree in computer science or information with six years of relevant experience. Technical Skillset: Python (pandas, numpy), R, SQL/Hadoop, Tensorflow/Keras/Huggingface, Github, unix/cmd, github, AWS/Azure/GCP Significant knowledge in machine learning and working with large data Ability to develop and optimize data science software Management of data infrastructure Experience working with multiple project and collaborating with teams Clear and timely communication Relevant education and experience may be substituted as appropriate. Preferred Qualifications Experience using Rest APIs and/or data scraping Knowledge of or experience with signal processing, computer vision, or network analysis Experience with open-source software/OSINT An ideal candidate should have experience with “big” data and cloud computing/infrastructure. Salary Range $80,000 + depending on qualifications Working Conditions Typical office environment Required Materials Resume/CV 3 work references with their contact information; at least one reference should be from a supervisor Letter of interest Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded. Once your job application has been submitted, you cannot make changes. Important for Current university employees and contingent workers: As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume. In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above. ---- Employment Eligibility: Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval. ---- Retirement Plan Eligibility: The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. ---- Background Checks: A criminal history background check will be required for finalist(s) under consideration for this position. ---- Equal Opportunity Employer: The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions. ---- Pay Transparency: The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information. ---- Employment Eligibility Verification: If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university. ---- E-Verify: The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university’s company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following: E-Verify Poster (English) [PDF] E-Verify Poster (Spanish) [PDF] Right To Work Poster (English) [PDF] Right To Work Poster (Spanish) [PDF] ---- Compliance: Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031. The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701. In 2024, The University of Texas at Austin was recognized as a 5 Year Champion having placed in the top 10 among Texas employers and top 15 for higher education institutions on Forbes’s list of 500 best large employers five years running. The University’s aspiration to become the world’s highest-impact public research university is driven by our outstanding people. Our employees are the bedrock of our university and are empowered to be true to themselves, to participate fully in our vibrant university, and to thrive as individuals. UT Austin offers competitive salaries, full benefits, an extensive support network, and above all, an enriching and highly collaborative working community that is deeply passionate about our vision for higher education and public service. Looking for a student job? Please see our Student Employment site. Comments and Inquiries: Email comments to: Human Resource Service Center. For questions or concerns regarding equal opportunity only, contact Equal Opportunity Services. Additional information for applicants can be found on the Human Resources web page: Applying for Employment. For more job information, call the Human Resource Service Center at (512) 471-4772, or toll-free at (800) 687-4178. UT Austin is a Tobacco-free Campus