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Vacante en Luxemburgo de ingeniero de investigación/ingeniera de investigación
Post-doctoral Researcher In Ai Benchmarking (m/f)
Clasificación del trabajo: Profesionales científicos e intelectuales › Profesionales de las ciencias y de la ingeniería › Ingenieros (excluyendo electrotecnólogos) › Ingenieros no clasificados bajo otros epígrafes › ingeniero de aplicaciones/ingeniera de aplicaciones › ingeniero de investigación/ingeniera de investigación.
Traducción de la profesión: Akademische Berufe › Naturwissenschaftler, Mathematiker und Ingenieure › Ingenieurwissenschaftler (ohne Elektrotechnik, Elektronik und Telekommunikation) › Ingenieure, anderweitig nicht genannt.
Descripción de la oferta de trabajo:
24 months contract | Belval
Are you passionate about research? So are we! Come and join us
The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.
Do you want to know more about LIST? Check our website: https://www.list.lu/
Discover our IT for Innovative Services department: https://www.list.lu/en/informatics/
How will you contribute?
Within the Trustworthy AI group, we are looking for a post-doctoral researcher with strong AI benchmarking expertise for a European Defence Funds project. If you are passioned about AI, research with a strong impact, and have an interest for working alongside world-class defence actors, let us know of your profile.
The ideal candidate would cover a mix of the following points
Definition of AI Metrics and Experimentation
· Semantic segmentation metrics: class- / task-specific and/or instance-level metrics, pixel-level, panoptic, metrics for resilience, and use-cases that target real-time and long-term performance evaluation, model complexity, …
· Hardware-specific AI metrics: inference speed, memory usage, power consumption, single/double-precision, performance on GPUs, TPUs, edge, …
Impact of Data on Performance
· Impact of data split and augmentation on model performance, overfitting, sensitivity to class imbalance, transfer-learning and fine-tuning performance
· Data augmentation for testing model resilience & re-assessment: occlusion, jittering, regularization techniques, geometric and/or photometric transformations, inpainting, …
· GAN-driven augmentation / adversarial synthetic data generation for challenging a model's performance, domain adaptation (e.g., image-to-image translation, style transfer augmentation)
· Temporal and spatial split: concept drift, train vs inference, class-aware split (low-representativeness class benchmarking, long-tail distribution), out-of-distribution generalization
Semantic Segmentation Explainability Benchmarking
Hyper-model / model sampling, latent model space metric learning
Reproducibility and metrics
Tooling; standardized benchmark protocol(s) and reporting
· Experience with tooling for AI model versioning, experiment tracking, MLOps & orchestration, containerization, model serving, REST APIs
· Reporting and support for post-benchmarking drill-down on results
We offer a highly dynamic environment as part of a team that is active across different technology-transfer areas (AI benchmarking, explainability, embedded/edge AI, …). LIST also offers a wide range of opportunities for training, as well as engaging with world-class researchers and labs.
Is Your profile described below? Are you our future colleague? Apply now!
The scope of the work is on AI benchmarking, while observing applications for semantic segmentation and anomaly detection.
The successful candidate will be responsible with conducting state-of-the-art research in the area of AI benchmarking for semantic segmentation / AI models, publishing in high-end journals and venues, operational work for the implementing metrics, benchmarking pipelines, etc., all in a solution-focused environment.
The successful candidate is expected to:
· Have a strong ML/AI background, hold a PhD in computer science, mathematics or similar, and be able to showcase a track record in AI benchmarking research.
· Hands-on experience and a track record of projects carried using frameworks like Pytorch and/or Tensorflow is an absolute must.
· Any experience in working with e.g. Kubeflow, Kubernetes / associated tooling, and benchmarking frameworks like MLPerf / others, is a plus while not a strong requirement.
Operational knowledge and fluency in English is mandatory; French can be a plus while not required nor mandatory.
Any previous experience in a defense-oriented context is a plus while not mandatory; similarly, having been granted an EU Personal Security Clearance in the past can be a strong advantage.
Your LIST benefits
An organization with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects
Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society
Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations in all that we do
An environment encouraging curiosity, innovation and entrepreneurship in all areas
Personalized learning programme to foster our staff's soft and technical skills
Multicultural and international work environment with more than 50 nationalities represented in our workforce
Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions
Gender-friendly environment with multiple actions to attract, develop and retain women in science
32 days' paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
Flexible working hours, home working policy and access to lunch vouchers
Apply online
Your application must include:
A motivation letter oriented towards the position and detailing your experience
A scientific CV with contact details
List of publications (and patents, if applicable)
Contact details of 2 references
Application procedure and conditions
We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting diversity and ensuring equal opportunities in our workforce. This information will be kept confidential and will not be used for any discriminatory purposes.
LIST is dedicated to maintaining an inclusive work environment and is an equal opportunity employer. We are committed to attracting, hiring, and retaining a diverse workforce. All applicants will be considered for employment without discrimination based on national origin, race, colour, gender, sexual orientation, gender identity, marital status, religion, age, or disability.
Applications will be continuously reviewed until the position is filled. An assessment committee will thoroughly evaluate applications, adhering to guidelines designed to ensure equal opportunities.
The primary criteria for selection will be the alignment of the applicant's existing skills and expertise with the requirements mentioned above.
País del trabajo: Luxemburgo.
Número de puestos: 1.
Experiencia: 1 años.
Empleador: Luxembourg Institute of Science and Technology - LIST.
Instrucciones para solicitar:
Oferta de trabajo obtenida del portal Eures, con fecha 17 de Julio de 2024, y con identificador de la vacante:PES_LU_725496.
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