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Declaration of interest regarding PhD project:
The department of Clinical Pharmacology, Pharmacy and Environmental Medicine (CPPEM) at SDU is looking for applicants for a PhD scholarship within the field of health science.
We are looking for a person with a relevant degree (MD, MSc. etc.)
Research environment
We offer an attractive, flexible and inspiring work environment with dedicated and highly skilled colleagues. As a department, we value having an informal culture and dialogue across all job functions at the department. Further, attracting and training excellent young researchers is a priority. In your daily work, you will report to assistant professor Iben Have Beck and professor Tina Kold Jensen but you will be expected to contribute to the whole research unit.
Project description
The PhD position is funded by a grant from the Novo Nordic Foundation to investigate the impact of early exposure to PFAS on puberty timing and neurodevelopment (assessed by neuropsychologists) within the Odense Child Cohort (OCC). PFAS levels have been measured during fetal life, and at 18 months and 5 and 7 years. The project does require biological knowledge and statistical skills. The successful applicant does not need to be familiar with these techniques but have a genuine interest in understanding biological mechanisms and statistics. The project is performed in close collaboration with child- and adolescent psychiatry specialists and researchers from the Department of Growth and Reproduction, so good collaboration skills are required.
The position is placed within CPPEM, which is a highly motivated research unit that performs research within pharmacology and environmental medicine. The research areas of CPPEM span from environmental medicine to pharmacoepidemiology, clinical studies and cell-based basic pharmacology. Collectively, CPPEM has a strong background in exposure to environmental chemicals, pharmacoepidemiology, pharmacogenetics, pharmacokinetics, drug-drug interactions and therapeutic drug monitoring. Specifically, the environmental medicine group studies the impact of early life exposures to environmental chemicals. Per- and polyfluoroalkyl substances (PFAS) are a main focus area, with studies of the adverse health effects of exposure, biomonitoring and advising national and international authorities.
Qualifications
We are looking for a candidate with a Master's degree or equivalent within Public Health, Medicine, Data Science or other fields related to Epidemiology or Environmental Medicine. The ideal candidate has prior experience in working with health data, is familiar with quantitative statistical analysis and has at least a basic understanding of statistical analysis framework or software. If you do not have any experience with the above but are interested in the topic, we still encourage you to apply, as we are mainly looking for a highly motivated individual that is willing to learn. Besides research, the PhD student is expected to help with the department's teaching obligations in accordance with his or her own background. We strongly encourage all applicants to apply, regardless of geographical location, age, gender, race, or religious beliefs. Only complete applications written in English will be accepted for evaluation.
For further information about the project, please contact
Department of Clinical Pharmacology, Pharmacy and Environmental Medicine (CPPEM)
University of Southern Denmark (SDU)
Additional information about the position can be obtained from professor Tina Kold Jensen (tkjensen@health.sdu.dk; +45 29464350) or assistant professor Iben Have Beck (ibeck@health.sdu.dk).
Applications must include:
• At letter stating the interest, motivation and qualifications for the project (max. 2 pages) - upload under “Application form”.
• Detailed CV, including personal contact information
• Certified copy of diploma (Master’s degree in a relevant field)
Shortlisting may be used in the assessment process.
Further information about the PhD-study can be found at the homepage of the University.
Applications must be submitted electronically using the link "Apply now". Attached files must be in Adobe PDF format. We strongly recommend that you read How to apply for a position at SDU before you apply.
Incomplete applications and applications received after the deadline will neither be considered nor evaluated. This also applies to reference letters.
Closing date 31th of Marts 2026
Successful candidates will be asked to send an application to the PhD Secretariat, Faculty of Health Sciences, to be enrolled as PhD students.
The PhD programme will be carried out in accordance with Faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order)
Salary and Working Conditions at SDU
PhD students employed at SDU are employed as PhD fellows according to the Danish Confederation of Professional Associations in public employment (AC) agreement.
Salary and any salary supplement are paid according to your seniority level and as negotiated with your union representative. The base salary (excluding 18.07% pension contribution) is DKK 374,912.98.
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
Imagine working with cutting-edge machine learning models, designing robust and scalable software infrastructure, and collaborating with dedicated colleagues — all while playing a key role in scaling our business even further.
Does this sound exciting? Then you might be our new Quant Infrastructure Engineer at Alipes Capital.
At Alipes Capital, we have been a market leader in automating financial markets since our inception in 2008, pioneering fully automated natural language processing systems to read and interpret financial news.
To accomplish our goal of being the best at what we do, we are focused on building a world-class ML engineering workflow, ensuring seamless training, deployment and monitoring of our predictive models.
As a core member of the Quant team, your work will be instrumental in developing the infrastructure enabling us to transform massive unstructured financial data sets into production-ready inference models that drive real-time trading decisions. You will work with technologies such as Python, Kubernetes, Ray and Airflow.
In doing so, you will get a chance to develop and maintain the infrastructure needed for scalable, high-performance ML systems, ensuring a seamless pipeline from dataset generation through model prototyping to production deployment.
Key responsibilities include:
Designing, optimizing and maturing our infrastructure to support distributed model training and experiment tracking, as well as further developing internal Python tools for smooth interaction
Building and automating robust data pipelines for dataset generation and feature engineering, while enabling data version control
Developing software for rapid experimentation and deployment, including automated testing, continuous integration, and delivery
Improve feature generation system- develop a feature store with definition and automated generation
Transitioning to a more structured table based dataset store
Implementing best practices in software development, ensuring maintainability, scalability, and efficiency of ML systems through automated testing and real-time monitoring,
Improving model deployment workflows, focusing on minimizing latency, ensuring reproducibility, and enabling fast iterations
You will get instant validation of your work and experience short feedback cycles, where going from inception to deployment can be a matter of hours. There will be no red tape to cut and no sales people to consult.
About the team
All of this will happen in an informal atmosphere where technical discussions are valued, and you are encouraged to take ownership of, and pride in, your work. You will impact the direction of the Quant team, prioritize your work and choose the tools that get the job done. We are a tight-knit modeling team with passionate quantitative researchers covering 9 nationalities – a mix of PhD’s and MSc’s with expertise in statistical analysis, mathematical modeling and machine learning. We enjoy collaboration and are always willing to lend a helping hand. We are working alongside two other teams of software developers and traders that implement and conceive the mathematical models together with us. What makes this constellation work great is that all of the individual team members write code and are willing to engage on a deep, technical level of understanding.
About you
A scientific and inquisitive mind
Fluency with computer science fundamentals, specifically data structures and algorithms
Experience working with ‘out-of-core’ datasets
Experience with Python, in particular the data preprocessing, ETL pipelines and distributed systems
Familiarity with strongly typed languages like C# or C/C++ or Rust
A few years of experience in production-grade environments working with Machine Learning based applications
Experience with distributed computing frameworks (for example Spark, Ray or Dask)
Familiarity with containerization technologies (for example Docker Compose or Kubernetes)
Nice to have
Experience working with the full Machine Learning stack and a strong MLOps foundation, going from dataset generation through model training and real-life validation and monitoring
Experience working with tools like PyTorch, Tensorflow, XGBoost and/or Catboost
Familiarity with algorithmic trading concepts
PhD or MSc degree in engineering, computer science, mathematics or physics
What we can offer you
Flat hierarchy and high levels of trust and autonomy
Exciting problems to solve
Collaborative team made up of really smart and curious people
Nice office in Nordhavn
Pension, Health Insurance and 30 days of vacation
Practicalities
To apply, please send us your CV. If your profile looks like a good match, we will get in touch to coordinate an online technical test as a first step in the interview process.
If you have specific questions about the role, you are welcome to email us at quant_jobs@alipescapital.com. Please do not send in your applications to this email address, as our interview team will not have visibility to review.
Le Chef Boucher est responsable de la préparation, de la découpe et de la mise en valeur des viandes et produits dérivés, ainsi que de la gestion de l'équipe et du respect des normes d'hygiène et de qualité. Il contribue également à la réalisation de préparations typiques des Balkans et à la satisfaction des clients grâce à son savoir-faire et son sens du service.
Tâches principales:
Production et préparation:
·Réaliser diverses préparations carnées balkaniques (keftas, saucissons, marinades, etc.).
·Préparer différents types de keftas (au fromage, à l'ail, aux épices...).
·Remplir les saucissons et assurer leur fumage à l'aide du fumoir (four à charcuterie).
·Utiliser le mélangeur, le poussoir, le fumoir et effectuer les découpes de viande selon les besoins.
·Veiller en permanence à l'hygiène, la propreté et la sécurité alimentaire.
Découpe et transformation:
· Sélectionner, désosser, parer et préparer les viandes selon les normes de qualité.
· Contrôler la traçabilité, la fraîcheur et la conformité des produits.
·la présentation en vitrine et la mise en valeur des produits carnés.
Gestion et encadrement:
·Organiser le travail de l'équipe (planification, répartition des tâches).
·Former et accompagner les bouchers et apprentis.
·Gérer les commandes, les stocks et les approvisionnements. en collaboration avec notre
superviseur boucher
·Suivre les ventes, assurer la rentabilité du rayon et proposer des améliorations.
Relation client:
·Accueillir, conseiller et fidéliser la clientèle.
·Promouvoir lesproduits maison et les spécialités balkaniques.
·Garantir un service de qualité et une présentation soignée.
Expérience confirmée dans une fonction similaire (chef boucher, boucher principal ou préparateur charcutier).
·Titulaire d'un diplôme en boucherie ou équivalent. ( 5 ans de l'expérience)
·Bonne condition physique (port de charges et travail debout prolongé).
·Maîtrise des techniques de découpe, désossage et préparation.
·Connaissances des outils de transformation : mélangeur, poussoir, fumoir, etc.
·Compétences linguistiques : français, arabe, rif.
·Sens du service client, du travail en équipe et plaisir de partager son savoir-faire.
·Respect rigoureux des règles d'hygiène et de sécurité.
Contrat à durée déterminée de 3 mois, éventuellement prolongeable, en vue d'un CDI
Travail à temps plein (38h/semaine), 5 jours par semaine
Plage horaire et jours de travail variable et à convenir avec le gérant
Le magasin est ouvert 6 sur 7 (fermeture le mercredi)