Master's thesis: Life Cycle Assessment of microwave graphitization process for battery applications

This is NTNU​ NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the application process here.     Video: https://youtu.be/Xt-yHCN5QS0About the position​ The Norwegian Center on AI for Decisions (aiD) has vacancy for a PhD fellowship in Predictive AI-Based Maintenance and Optimization of Building Energy Management Systems​. aiD is one of the new Norwegian AI research initiatives, funded by the Research Council of Norway and industry partners. It consists of 13 research partners and more than 60 partners from industry and public sector led by NTNU and SINTEF. All open positions will be cross-linked on the aiD website aid-center.no  About the Position​ Are you passionate about artificial intelligence, digital twins, and energy management systems in buildings? We are offering a fully funded, three-year PhD position to develop a cutting-edge AI decision-support tool for predictive maintenance and optimization of building energy management systems and technologies (i.e., Heating, Ventilation and Air Conditioning - HVAC). Partnering with Statsbygg, the Norwegian Government’s Building Agency, your research will be deployed across a massive portfolio of public buildings. Moving beyond outdated calendar-based maintenance schedules, your mission is to solve a critical economic and environmental timing problem: knowing exactly when it becomes cost-optimal to intervene in degrading or overloaded systems. You will overcome the scarcity of real-world fault data by combining Simulation-Based Inference (SBI) and Building Performance Simulation (BPS). By integrating historical facility management (FDVU) records with live building sensor data, you will train AI models to recognize abnormal performance patterns, quantify quality-adjusted service life, and autonomously recommend whether a system needs maintenance, recalibration, or a capacity upgrade.  Your immediate leader will be the Head of Department. About the project​ This position is hosted at the aiD Center​, a premier research hub dedicated to advancing the role of artificial intelligence in complex decision-making processes. Hosted by the Norwegian University of Science and Technology (NTNU) and SINTEF aiD bridges technological, organizational, and human-centric gaps to foster a society where AI-driven value creation is safe and ethical. As an aiD-PhD candidate, you will collaborate closely with academic experts and industry leaders ensuring your research translates directly into portfolio-scale impact for the future of national real estate. You will be working with a multidisciplinary team of experts in building systems, artificial intelligence and decision-making. The supervision team includes:   • Prof. Ivan Depina – main supervisor and coordinator, probabilistic modelling, scientific machine learning • Prof. Mohamed Hamdy – building performance simulation, building automation systems, and multi-objective optimization. • Prof. Freja Nygaard Rasmussen – life cycle assessment • Prof. Sebastien Gros – decision-making, energy use, AI and machine learning • Dr. Signe Riemer-Sørensen - AI and machine learning, hybrid analyses • Prof. Ahmed Kedir Mohammed – data analysis and machine learning Duties of the position​ • Complete the doctoral education until obtaining a doctorate • Carry out research of good quality within the framework described above • Academic publications and popular science dissemination • Participate in the aiD research network and engage with Statsbygg • Contribute to research and knowledge exchange activities at the department • Participate in international activities such as conferences and/or research stays abroad • Contribute to supervision activities if required Be prepared for changes to your work duties after employment. Required selection criteria​ • You must have a relevant master’s degree in civil engineering, mechanical power engineering or a related field. Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained at master's level • You must have a strong academic background from your previous studies and have an average grade from your Master's degree study, or equivalent education, which is equal to B or better compared to NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker grade background, you may be considered if you can document that you are particularly suitable for a PhD education • You must meet the requirements for admission to the Doctoral Programme - PhD - Faculty of Engineering Science - NTNU • Good written and oral communication skills in English  PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application”. The appointment is to be made in accordance with NTNUs guidelines for recruitment positions for general criteria for the position. Preferred selection criteria​ • Machine Learning Expertise: A robust foundation in probabilistic modeling, Bayesian inference, deep learning, and/or anomaly detection • Modeling & Simulation Experience: Familiarity with Building Performance Simulation (BPS) tools, such as EnergyPlus or IDA ICE • Building Automation System (BAS) and Building Energy Management (BEM) • Data Integration Proficiency: Ability to work with complex, heterogeneous data streams • Domain Knowledge Advantage: Familiarity with building energy systems, HVAC operations, or fault detection and diagnosis (FDD) is considered a strong asset • Work Experience: Relevant work experience in operation and maintenance of buildings • Communication skills: Good oral and written presentation skills in Norwegian or another Scandinavian language equivalent to level B2-C Personal characteristics​ To complete a doctoral degree (PhD), it is important that you are able to:  • Work independently • Work in a structured way, set goals and make plans to achieve them • Present and discuss your research with other professionals • Get involved and contribute constructively with feedback • Work constructively under pressure or in the face of adversity  • Show curiosity and strong motivation for the subject • Analyze data, assess different perspectives and draw well-founded conclusions  • Be flexible and open to adjusting the plan for the project as needed Emphasis will be placed on personal qualities. We offer​ • An exciting job with an important mission in society • Developing tasks in a strong and international professional environment • Career guidance and follow-up during the PhD period • Open and inclusive working environment with committed colleagues • Working capital that can be used to implement the project • Mentor programme as a new employee at NTNU • Favorable terms as a member of the Norwegian Public Service Pension Fund (SPK) • Free Norwegian language training at a basic level (A2) As a PhD Candidate at NTNU, you will have access to employee benefits. Diversity​ Diversity is a strength, and at NTNU we aim to be an employer that reflects the diversity in society and that makes use of the potential of the population's collective skills. Our vision is Knowledge for a better world and our values ​​are creative, critical, constructive and respectful. We believe that an organization that is equal, diverse and gender-balanced is essential for us to achieve our goals.  We strive to attract employees with different skills, life experiences and perspectives to contribute to even better problem solving of our societal mission in research and education.  If you think this position is relevant and interesting, we encourage you to apply, regardless of gender, functional ability and cultural background, or whether you have been out of work for a period of time. At NTNU we want to increase the proportion of women in scientific positions. We have a number of measures to promote equality.  Salary and conditions​ In the position of PhD Candidate, code 1017, your gross salary will normally be NOK 550 800,-per annum depending on qualifications and seniority. A 2% statutory contribution to the State Pension Fund is deducted from the salary.  The employment period is 3 years for the doctoral work. For employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme PhD in Engineering (Doctoral Programme) 3 years - Trondheim - NTNU within three months of your employment contract start date, and that you participate in an organized doctoral programme throughout the period of employment. The position is conditional on external funding. As an employee at NTNU, it is important that you keep yourself up to date with academic and organizational changes and adapt to them. For the necessary professional and social interaction, it is a prerequisite that you are physically present and available to the institution on a daily basis. The appointment is carried out in accordance with the principles of the State Employees Act, and Export control (legislation that regulates the export of knowledge, technology and services). Candidates who, after assessment of the application and attachments, are considered to bein conflict with the criteria in the latter act, will not be able to be employed. About the application​ The attachments (including a description of your scientific work) must accompany the application as these documents form the basis of the application assessment. The documents must be in Norwegian/a Scandinavian language or English.  Please note: the application will only be assessed on the basis of the information we have received by the application deadline. Therefore, make sure that your application clearly shows how your skills and experience meet the criteria described above. The application and all attachments must be sent electronically via Jobbnorge.no. If you are invited to an interview, you must bring certified copies of certificates and diplomas upon request. The application must include: • Transcripts and diplomas for Bachelor's and Master's degrees • CV  • Copy of Master's thesis. If you have recently submitted your Master's thesis, you can attach a draft of the thesis. Documentation of a completed Master's degree must be presented before taking up the position. • Project outline containing proposals for an overall description of research questions, theoretical perspectives, methodological design for the project and progress plan (maximum 1500 words/4 pages)  • Short letter of motivation (400 words/1 page) • Possibly publications etc. other relevant research work • Possibly certificates • Names and contact information of three relevant referees If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both Bachelor's and Master's education, in addition to other higher education. If your institution uses “diploma supplement” (normal for most European institutions), you must attach this. A description of the documentation required can also be found here. If you already have a statement from Norwegian Directorate for Higher Education and Skills (HK-dir), please attach this as well. Joint work will be considered. If it is difficult to identify your contribution to joint work, you must attach a brief description of your participation. When assessing the best qualified, we emphasize necessary qualifications such as education, experience and personal suitability. Motivation for the position, ambitions, and potential for research will also count when assessing the candidates. NTNU recognizes a wide range of academic contributions and has committed itself to The San Francisco Declaration on Research Assessment and CoARA (responsible assessment of research and recognition of a greater breadth of academic contributions in accordance with NTNU's social mission). General information​ A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you wish to be exempt from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation. You will be notified if the exemption is not granted. If you think this position looks interesting and in line with your qualifications, you are welcome to apply. If you have any questions about the position, please contact Associate Professor Ivan Depina, 40389387, ivan.depina@ntnu.no and Professor Mohamed Hamdy, mohamed.hamdy@ntnu.no   If you have any questions about the recruitment process, please contact Ragne Matberg (HR Consultant), email: ragne.matberg@ntnu.no Application deadline: 16.08.2026​ ----------------- For practical information about working at NTNU, please visit this webpage.    The city of Trondheim​ is a modern European city with a rich cultural scene. Trondheim is the tech capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.

DDLS INDUSTRIAL PHD POSITION We are announcing a position for a Data-Driven Life Science (DDLS) PhD student in data-driven precision medicine and diagnostics. To be a doctoral student means to devote oneself to a research project under supervision of experienced researchers and following an individual study plan. A doctoral degree corresponds to four years of full-time study. This is an industry PhD project which is a collaboration between the Karolinska Institute, SciLifeLab and Ribocure Pharmaceuticals AB. The PhD student will be employed by Ribocure Pharmaceuticals AB but admitted to PhD studies at the Karolinska Institute. The studies will primarily take place at the Karolinska Institute and SciLifeLab in Stockholm, with frequent research internships at Ribocure Pharmaceuticals AB in Gothenburg. We offer a creative and inspiring environment full of expertise and curiosity. The Karolinska Institute is one of the world's leading medical universities. Our vision is to pursue the development of knowledge about life and to promote a better health for all. At the Karolinska Institute, we conduct successful medical research and hold the largest range of medical education in Sweden. As a doctoral student you are offered an individual research project, a well-educated supervisor, a vast range of elective courses and the opportunity to work in a leading research group. Tbe Karolinska Institute collaborates with prominent universities from all around the world, which ensures opportunities for international exchanges. Ribocure Pharmaceuticals AB, based in Gothenburg, is a clinical‑stage biotech company developing innovative siRNA‑based therapies. Our research focuses on areas with high unmet medical need, including cardiovascular, metabolic, liver, and kidney diseases. We have access to a strong and vertically integrated platform in oligonucleotide research, spanning from early discovery to clinical development. Our goal is to turn cutting‑edge science into new medicines for patients. The PhD project will be embedded in a close collaboration with Ribocure, providing the candidate with valuable exposure to industrial drug development, insight into how academic discoveries are translated into medicines, and experience of working at the interface between fundamental research and therapeutic innovation. PROJECT DESCRIPTION Project title: "RIBO-LINC: Linking data-driven solutions and RNA innovation for liver and cardiometabolic health". An exciting opportunity is available to join a cutting-edge project at the interface of AI, multi-omics, and RNA therapeutics, aiming to transform precision medicine for cardiometabolic and liver diseases. Current therapeutic strategies largely operate at the gene level, overlooking the functional diversity generated by alternative splicing. This project addresses this critical gap by developing data-driven approaches to identify and prioritize isoform-specific therapeutic targets, enabling a new level of precision in RNA-based treatments. The project will combine large-scale multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta-cohort and perturbation datasets, the work aims to uncover isoform-level regulatory mechanisms and guide the development of next-generation RNA therapeutics with improved specificity and reduced off-target effects. Importantly, computational predictions will be directly linked to experimental evaluation of GalNAc-conjugated RNA therapeutics. This position offers a unique opportunity to work in a highly interdisciplinary environment, contributing to the development of transformative therapies at the forefront of AI-driven biomedical research. QUALIFICATION REQUIREMENTS To be admitted to postgraduate education, the applicant must meet the general and specific entry requirements. The qualification requirements must be met by the deadline for applications. You meet the (A) general entry requirements if you: 1. have been awarded a second-cycle/advanced/master qualification (i.e. master degree), or 2. have satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the advanced/second-cycle/master level, or 3. have acquired substantially equivalent knowledge in some other way in Sweden or abroad.* Follow the instructions on the web page Entry requirements (eligibility) for doctoral education. *If you claim equivalent knowledge, follow the instructions on the web page Assessing equivalent knowledge for general eligibility for doctoral education. To meet the (B) specific entry requirements, the applicant must have 1. credits in Life Science, Computer Science Mathematics, Physics or Bioinformatics or alike, including a 30 credit Degree Project (thesis). 2. proficiency in English equivalent to the course English B/English 6 at Swedish upper secondary school. Follow the instructions on the web page English language requirements for doctoral education. Verification of your documents: The Karolinska Institute checks the authenticity of your documents and reserves the right to revoke admission if supporting documents are discovered to be fraudulent. Submission of false documents is a violation of Swedish law and is considered grounds for legal action. Additional preferred qualifications: * Prior experience with bioinformatics workflows and analysis of large-scale multi-omics datasets (e.g., RNA-seq, proteomics, long-read sequencing). * Familiarity with machine learning approaches, particularly artificial neural networks, and their application to biological data. * Experience with workflow management systems (e.g., Snakemake, Nextflow) and reproducible data processing pipelines. * Knowledge of transcriptomics and alternative splicing analysis, including isoform-level quantification tools. * Programming skills in R and/or Python, with experience in data integration and statistical analysis. * Exposure to RNA therapeutics or functional genomics approaches is an advantage. * Strong interest in interdisciplinary research combining computational biology with experimental validation. SELECTION The selection among eligible candidates will be based on their ability to successfully complete the PhD studies. Key criteria include analytical thinking, the capacity to work independently and collaboratively, as well as creativity, initiative, and a strong interest in interdisciplinary research. The assessment will be based on: * Technical Expertise: Documented experience in R and/or Python, with proficiency in bioinformatics and analysis of multi-omics datasets (e.g., RNA-seq, proteomics, long-read sequencing). Familiarity with machine learning approaches, particularly neural networks, and experience with workflow management systems (e.g., Snakemake, Nextflow). Knowledge of transcriptomics and alternative splicing analysis. * Academic and Research Excellence: Demonstrated high-quality academic performance, including strong grades and relevant degree projects. Prior research experience in computational biology, functional genomics, or related fields will be highly valued. * Soft Skills and Research Attributes: Excellent written and oral communication skills in English, strong analytical and problem-solving abilities, and the capacity to work both independently and in collaborative, interdisciplinary environments. Creativity, initiative, and a structured approach to complex data analysis are essential. * Motivation and Fit: A well-articulated motivation letter describing the candidate’s interest in AI-driven multi-omics integration and RNA therapeutics. The candidate should demonstrate enthusiasm for bridging computational and experimental research. Final evaluation will include interviews and reference checks to assess overall fit and potential. TERMS AND CONDITIONS The doctoral student will be employed at Ribocure Pharmaceuticals with affiliation to Karolinska Institute on a doctoral studentship maximum 4 years full-time. APPLICATION PROCESS Submit your application and supporting documents through Ribocure Pharmaceuticals AB recruitment system. We prefer that your application is written in English, but you can also apply in Swedish. Deadline to apply is August 2nd 2026. Your application must contain the following documents: * A personal letter and a curriculum vitae * Degree projects and previous publications, if any * Any other documentation showing the desirable skills and personal qualities described above * Documents certifying your general eligibility (see A above) * Documents certifying your specific eligibility (see B above) DDLS AND THE SCILIFELAB SciLifeLab is a national center for molecular biosciences with a focus on health and environmental research. The center combines frontline technical expertise with advanced knowledge of translational medicine and molecular bioscience. SciLifeLab is a national resource hosted by Karolinska Institutet, KTH Royal Institute of Technology, Stockholm University and Uppsala University. The center also collaborates with several other universities. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims to recruit and train the next generation of data-driven life scientists and to create globally leading computational and data science capabilities in Sweden. The program is funded with a total of 3.3 billion SEK over 12 years from the Knut and Alice Wallenberg (KAW) Foundation. In 2026 the DDLS Research School will be expanded with the recruitment of 25 academic and 7 industrial PhD students. During the course of the DDLS program more than 260 PhD students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ The future of life science is data-driven. Will you be part of that change? Then join us in this unique program! USEFUL LINKS Ribocure Pharmaceuticals AB Claudia Kutter Research group at the Karolinska Institute and SciLifeLab DDLS Research School FOR ANY QUESTIONS REGARDING THE POSITION PLEASE CONTACT: JULIA GRÖNROS, PHD PROJECT DIRECTOR EXTERNAL INNOVATION JULIA.GRONROS@RIBOCURE.COM RIBOCURE PHARMACEUTICALS AB ______________________________________ CLAUDIA KUTTER PRINCIPAL INVESTIGATOR CLAUDIA.KUTTER@KI.SE KAROLINSKA INSTITUTE