Dallas Baptist University
About Dallas Baptist University
Basic information and contact details for Dallas Baptist University
Dallas Baptist University, founded in 1898 as Decatur Baptist College, is a Christian liberal arts college in Texas, US.
The university offers over 70 undergraduate majors across its College of Business, Mary C. Crowley College of Christian Faith, Dorothy M. Bush College of Education, College of Fine Arts, College of Humanities and Social Sciences, College of Natural Sciences and Mathematics, College of Professional Studies, Gary Cook School of Leadership. You can choose between majors such as Biblical or Christian Studies, Mathematics, Philosophy, Art, Graphic Design, Piano Performance, Criminal Justice, Sociology, Natural Sciences, Marketing, Accounting and others.
In addition, the college offers 29 master’s programmes, two doctoral programmes, seven associate degrees and 55 accelerated bachelor’s and master’s degree programmes.
The university’s declared purpose is to develop nine main competencies - reading comprehension, logic and critical thinking, written and oral communication, computer and tech skills, Christian worldview, responsible citizenship, integrated service-learning, physical and emotional wellness and information literacy.
Athletics, parties (some including bonfires), fraternities and sororities make the non-academic student life at DBU on campus. The 292-acre campus is located within 13 miles of the centre of Dallas, and the university is just 19 miles from Forth Worth, so students can easily benefit from the cities’ night life, cultural events and infrastructure.
A few notable alumni of DBU are Christian music artist Kari Jobe, former Texas secretary of state Gwyn Shea and Member of the Texas House of Representatives Ron Simmons.
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VANGUARD - Postdoc in Network Tensor Completion
Mohammed VI Polytechnic University
Morocco
Mohammed VI Polytechnic University
Morocco
About Mohammed VI Polytechnic University (UM6P): Located at the heart of the Green City of Benguerir, Mohammed VI Polytechnic University (UM6P), a higher education institution with an international standard, was established to serve Morocco and the African continent and to advance applied research and innovation. This unique university, with state-of-the-art infrastructure, has woven an extensive academic and research network, and its recruitment process is seeking outstanding academics and professionals to promote Morocco and Africa’s innovation ecosystem. About the department Vanguard works on the development of innovative and interdisciplinary applied research projects. From technological innovation to the transfer of research to industry, Vanguard has also the mission of developing an ecosystem of related start-ups. For more information about our Center, please visit our webpage: https://vanguard.um6p.ma/ Offer description: There are many systems of interest to scientists that are composed of individual parts or components linked together in some way. Examples include the Internet, a collection of computers linked by data connections, human societies, which are collections of people linked by acquaintance or social interaction, transportation systems and biological interactions. These systems are represented as networks. A network is a set of objects that are connected to each other in some fashion. Mathematically, a network is represented by a graph, which is a collection of nodes that are connected to each other by edges. The nodes represent the objects of the network and the edges represent relationships between objects. A common way to represent a graph is to use the adjacency matrix associated with the graph. However, adjacency matrices only model networks with one kind of objects or relations between the objects. Many real world networks have a multidimensional nature such as networks that contain multiple connections. For instance, transport networks in a country when considering different means of transportation. The train and bus routes are different types of connections and should in some models be represented by different kinds of edges. These kind of situations can be modeled using multilayer networks which emphasize the different kind or levels, known as layers, of connections between the elements of the network and the interactions between these levels as well. In order to capture the structure and complexity of relationships between the nodes of networks with a mul-tidimensional nature, tensors are used to represent these kind of networks. For example, the transport network mentioned earlier would be represented by a 4th order tensor A 2RN_L_N_L where L is the number of the layers (transportation means) and N is the number of nodes (stations or stops). Using convenient tensor products, the goal is to define measures to analyze different multidimensional networks based on their adjacency tensors. However, collecting all the interactions in the systems and sometimes even observing all the components is a challenging task. In most cases, only a sample of a network is observed. Therefore, network completion needs to be addressed. Matrix completion methods have proved to be efficient when reconstructing a non fully observed data. These methods can be applied to complete or predict links in a network. However, missing information in a network can include both missing edges and nodes which makes classical matrix completion method insufficient. However,we may collect other information and features about the elements of the network. Therefore, side information about the nodes along with the observed edges need to be exploited. The problem of network completion arrises also for applications where the network has a multidimensional representation such as multiplexes and multilayer networks. Since multidimensional networks can be represented by tensors, one can think of applying tensor completion methods which have proved to be efficient in many applications such as image and video reconstruction. However, the same issue arises, tensor completion methods can not be directly applied to recover the links of the network giving the fact that the data is sparse most of the time. We aim to use auxiliary information about the multiplex and multilayer networks alongside with the observed links in order to predict or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor minimization and tensor decompositions paired with auxiliary information in order to recover missing links in a multilayer network with connected components. An important constraint in network completion is that the factorization must only capture the non zero entries of the tensor. The remaining entries are treated as missing values, not actual zeros as is often the case in sparse tensor and matrix operations. Therefore, the next step in this project is to address sparse optimization for tensors. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing multidimensional networks by studying the theoretical foundations behind randomized algorithms in the context of sparse optimization and applications in real world data sets. We are also interested in exploring opportunities for parallelism of the completion process, highlighting the potential for significant speedup in computations. Job responsibilities Research and Development: Conduct research to develop novel algorithms and methodologies for tensor completion in multidimensional networks. This includes exploring optimization techniques, tensor decompositions, and incorporating auxiliary information for more accurate completion. Algorithm Design: Design and implement algorithms for tensor completion, considering the unique challenges posed by sparse and multidimensional network data. This involves developing efficient and scalable algorithms that can handle large-scale datasets. Tensor Analysis: Analyze the structure and properties of multidimensional networks represented as tensors. Investigate different measures and metrics for characterizing network connectivity and relationships. Sparse Optimization: Address the challenge of sparse optimization for tensors by integrating randomized algorithms into optimization frameworks. Study the theoretical foundations of randomized algorithms in the context of sparse tensor operations and apply them to real-world datasets. Parallel Computing: Explore opportunities for parallelism in the tensor completion process to enhance computational efficiency. Investigate parallel algorithms and architectures that can exploit the inherent parallelism in tensor operations. Collaboration: Collaborate with interdisciplinary teams including computer scientists, statisticians, and domain experts to apply tensor completion techniques to real-world applications, especially in the case of social sciences. This involves effective communication and coordination to ensure the successful integration of mathematical methods into practical systems. Publication and Dissemination: Publish research findings in top-tier journals and present results at conferences and workshops. Disseminate knowledge and contribute to the academic community by sharing insights and methodologies developed during the course of the project. Mentorship and Training: Provide mentorship and guidance to graduate students and junior researchers involved in related projects. Share expertise and knowledge in applied mathematics, tensor analysis, and network science to foster the professional development of team members. Qualifications and experience essential PhD in Applied Mathematics in the fields of Numerical Linear Algebra, or equivalent. Prior experience on the subject is highly desired.
Salary
Competitive
Posted
13 Mar 2026
GTI - Postdoctoral Researcher – AI/ML for Energy Systems
Mohammed VI Polytechnic University
Morocco
Mohammed VI Polytechnic University
Morocco
Job Title: Postdoctoral Researcher – AI/ML for Energy Systems Location: Ben Guerir Position Type: Postdoctoral Research Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in its fields. The University is engaged in economic and human development and puts research and innovation at the forefront of African development. A mechanism that enables it to consolidate Morocco's frontline position in these fields, in a unique partnership-based approach and boosting skills training relevant for the future of Africa. Located in the municipality of Benguerir, in the very heart of the Green City, Mohammed VI Polytechnic University aspires to leave its mark nationally, continentally, and globally. The Green Tech Institute at Mohammed VI Polytechnic University (UM6P), Benguerir, Morocco, is seeking a highly motivated postdoctoral researcher to join our team in exploring the intersection of energy transition, circular economy, and sustainable construction production. This position aims to advance innovative solutions that promote sustainability in the built environment, focusing on the effective integration of renewable energy, resource efficiency, and waste reduction. The candidate must hold a PhD in Urban or Rural Development, Civil Engineering or related domain. The candidate is expected to have hands-on experience in field related to urban or rural planning, renewable energy and sustainable construction. Position Overview: We are seeking a talented and motivated Postdoctoral Researcher to join our cutting-edge team, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be on creating and optimizing state-of-charge (SOC) and state-of-health (SOH) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities: Develop and implement machine learning algorithms for SOC and SOH estimation. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics for real-time battery health monitoring and fault detection. Collaborate with embedded systems and hardware engineering teams to integrate AI models into the BMS. Optimize AI/ML pipelines for resource-constrained environments, including edge AI applications. Guide PhD students and collaborate with engineers to implement advanced ideas. Author scientific publications, present findings at conferences, and contribute to patents or technical innovations. Qualifications: PhD in Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, or a related field. Strong experience in developing and applying AI/ML models to energy systems or similar applications. Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on expertise in programming languages such as Python, R, or MATLAB. Solid understanding of battery systems, electrochemical processes, or energy management. Preferred Skills: Experience with time-series analysis, predictive modeling, and anomaly detection. Familiarity with real-time applications of AI/ML in embedded or IoT devices. Knowledge of cloud-based computing platforms for data processing (e.g., AWS, Google Cloud) Understanding of BMS architecture and electric mobility systems.
Salary
Competitive
Posted
13 Mar 2026
COLCOM - Postdoctoral Fellow Position in Omics and Soil Microbiome Research
Mohammed VI Polytechnic University
Morocco
Mohammed VI Polytechnic University
Morocco
Postdoctoral fellow Position in Omics and Soil Microbiome Research (2 years) The Mohammed VI Polytechnic University (UM6P) invites applications for a Postdoctoral fellow position to join an interdisciplinary research project focused on metaproteomic analysis of soil microbial communities. This project aims to identify key genes and enzymes involved in mitigating salinity stress and improving soil health and crop productivity. These positions are part of a broader initiative to develop biofertilizers and sustainable agricultural strategies to combat soil degradation and salinization. Research will involve state-of-the-art metaproteomics, bioinformatics, and functional microbiome studies conducted in field trials, greenhouse experiments, and laboratory settings. This role will focus on the interactions between rhizosphere microbiota and plant roots, investigating how microbial enzymes enhance plant stress tolerance under salinity conditions. The successful candidate will: Conduct metaproteomic and genomic sequencing of microbial communities associated with plant roots. Identify microbial enzymes and functional pathways involved in nutrient acquisition and stress adaptation. Analyze plant-microbe interactions in response to salinity stress. Collaborate on biofertilizer development incorporating beneficial microbial enzymes. Required Qualifications: Ph.D. in Microbiology, Bioinformatics, Soil Science, Plant Science, Environmental Science, or a related field. Expertise in microbiome data analysis, metagenomics, or metaproteomics. Proficiency in bioinformatics tools for multi-omics data processing Strong publication record in relevant fields. Ability to work in a multidisciplinary team and collaborate across research groups. Preferred Qualifications: Experience in functional characterization of microbial enzymes. Familiarity with microbial ecology and soil biochemistry in stress adaptation. Background in field and greenhouse experimental design. Application Process: Applicants should submit the following documents: Cover letter detailing research interests and relevant experience. Curriculum Vitae (CV) with a full list of publications. Contact information for three references. For inquiries, please contact achraf.elalali@um6p.ma
Salary
Competitive
Posted
13 Mar 2026
COLCOM - Postdoctoral Researcher in Genomic Language Models for Bacterial Genomes
Mohammed VI Polytechnic University
Morocco
Mohammed VI Polytechnic University
Morocco
Location: University Mohammed VI Polytechnic, College of Computing, Bioinformatics Laboratory, Ben Guerir, Morocco. Duration: 2 years About the Lab/Institution: The Bioinformatics Laboratory conducts research in the fields of bioinformatics, computational biology and computational chemistry and serves the agricultural, environmental and health sectors. The lab also provides bioinformatics consulting and data management services to UM6P researchers and their collaborators. UM6P has state of the art NGS sequencers and mass spectrometry and the largest HPC (High Performance Computing) cluster in Africa. The laboratory aims to leverage these resources to address bioinformatics needs internally and at the African level and to develop innovative research and training programs. For more information about the laboratory, you can visit https://bioinformatics.um6p.ma/ Project Description: We are seeking a highly motivated and talented postdoctoral researcher to join our team to develop a novel GPT-like system for bacterial genomes using cutting-edge genomic language models. This project aims to adapt and extend transformer-based architectures to create a powerful tool for understanding and predicting bacterial genomic sequences. The successful candidate will play a key role in developing and optimizing these models, applying them to diverse bacterial use cases, and contributing to the development of software tools for the broader research community. Responsibilities: Develop and implement transformer-based genomic language models for bacterial genome analysis. Train and evaluate models on large-scale bacterial genomic datasets. Apply the developed models to address specific research questions, such as gene function prediction, antibiotic resistance analysis, and evolutionary studies. Analyze and interpret results, and prepare manuscripts for publication in peer-reviewed journals. Collaborate with other researchers within the lab and external collaborators. Maintain accurate and organized records of research activities. Qualifications: Ph.D. in Bioinformatics, Computational Biology, Computer Science, Genomics, or a related field. Strong background in machine learning, particularly deep learning and natural language processing. Experience with transformer-based architectures (e.g., BERT, GPT) is highly desirable. Proficiency in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch). Experience with bioinformatics tools and genomic data analysis. Strong programming and data analysis skills. Excellent communication and writing skills. Ability to work independently and as part of a team. Preferred Qualifications: Experience working with bacterial genomic data. Knowledge of bacterial genetics and evolution. Experience developing software tools for bioinformatics applications. Experience with cloud computing platforms. To Apply: Please submit the following materials Cover letter outlining your research interests and experience. Curriculum vitae (CV) including a list of publications. A brief research statement describing your past research and future interests. Contact information for three professional references.
Salary
Competitive
Posted
13 Mar 2026
SUSMAT-RC - Post-Doctoral in Advanced Sustainable Materials for Sensing Applications
Mohammed VI Polytechnic University
Morocco
Mohammed VI Polytechnic University
Morocco
Job description: Sustainable Materials Research Center (SUSMAT-RC) is seeking a highly motivated and talented postdoctoral fellow to join our research team focused on the development of innovative and sustainable sensor systems for industrial applications. This position offers an exciting opportunity to contribute to cutting-edge research in the field of sustainable materials to develop promising solutions that support and promote smart and sustainable practices in industrial processes. The successful candidate will develop innovative and efficient sensing platforms using advanced manufacturing techniques and strategies. The sensor platforms will leverage miniaturized, low-cost, and efficient components, utilizing state-of-the-art manufacturing techniques to enable seamless integration into industrial equipment and infrastructure. Key duties: The successful candidate is expected to: Have strong experience in polymers, molecularly imprinted polymers, and polymer-based nanocomposite synthesis, characterization, and application. Demonstrate knowledge and/or experience in sensor processing including design, fabrication, and characterization. Conduct research to design, develop, and optimize sensors for industrial applications. This includes exploring novel sensing technologies, materials, and data analysis techniques. Conduct rigorous field testing of developed sensors to ensure sensor accuracy, reliability, and robustness. Collaborate with interdisciplinary teams, including engineers, and data scientists, to integrate sensor technologies into comprehensive industrial systems. Maintain detailed records of experimental procedures, results, and observations. Prepare technical reports, research papers, and presentations for conferences and scientific publications. Contribute to the generation of new research ideas, participate in grant writing activities, and seek external funding opportunities to support ongoing research projects. Have a good knowledge of analytical techniques (GC/LC-MS, HPLC, etc), spectroscopic techniques (UV-Vis, FTIR, Raman, NMR, XRD, spectrophotometry, etc), and microscopy techniques (SEM, TEM, AFM, etc) necessary for structural and physical-chemical characterization of polymer and polymer-based nanocomposite. Proven experience and familiarity with electrochemical techniques necessary for preparation, characterization and application of polymer and polymer-based nanocomposite: CV, LSV, DPV, SWV, EIS, etc. Broad experience in surface modification of inorganic or organic substrates. Contribute to the group’s activities in the processing of sustainable materials, (bio)polymer composites and their applications as sensing platforms in related fields. Experience in supervising undergraduate, master's and doctoral students. Criteria of the candidate To be considered for this role, you will ideally have: Ph.D degree in analytical chemistry, polymer science, materials science and engineering or any related field. Strong motivation and passion for research in the field of sensors Strong initiative, self-motivated, and focused on achieving quality outputs. Good time management and task prioritization skills. Strong analytical, problem solving and teamwork skills. Ability to work both as part of a team and to work independently. Excellent oral and written communication skills in English. Application and Selection Application folder must contain: Detailed CV. Motivation letter, emphasizing your specific interest and motivation A brief research statement. Contact information of 2 referees. About Mohammed VI About Mohammed Polytechnic University (UM6P): Located at the heart of the Green City of Benguerir, Mohammed VI Polytechnic University (UM6P), a higher education institution with an international standard, was established to serve Morocco and the African continent and to advance applied research and innovation. This unique university, with state-of-the-art infrastructure, has woven an extensive academic and research network, and its recruitment process is seeking outstanding academics and professionals to promote Morocco and Africa’s innovation ecosystem. About the Sustainable Materials Research Center (SusMat - RC): The Sustainable Materials Research Center (SusMat - RC) is a multidisciplinary research center engaged in the development of advanced biobased products and materials thereof using biotechnological, physical and chemical conversion strategies and engineering processes (b) understanding and controlling their underlying specific functionalities and the structure-properties relationship acting over multiple length scales from the molecular, nano to the macro level and their cross-interactions and (c) utilizing the gathered knowledge and the invented materials to address key technological challenges in Morocco and African continent and assist the transition toward a green and circular economy.
Salary
Competitive
Posted
13 Mar 2026
