Merge pull request #9 from mlinpl/groups_update

add new labs

_labs/BioMedIA.md

@@ -0,0 +1,10 @@
+---
+short_name: BioMedIA
+title: Oxford Biomedical Image Analysis (BioMedIA) cluster
+head: Bartek Papież
+contact: bartlomiej.papiez@bdi.ox.ac.uk
+website_url: https://eng.ox.ac.uk/biomedical-image-analysis/
+location: University in Oxford, England
+---
+
+The Oxford Biomedical Image Analysis (BioMedIA) cluster is an academic group of faculty, postdoctoral researchers, software engineers, support staff and research students that develop medical imaging and image analysis algorithms and tools that aim to improve image-based diagnostics, therapies and monitoring technologies in hospitals and primary care, and for both western world and global health care settings. The breadth of our interests span all major clinical imaging modalities (particularly magnetic resonance imaging, ultrasound imaging, endoscopy imaging, histopathology), multi-modal imaging (imaging and audio, imaging and gaze tracking, imaging and electrocardiogram) and microscopy. We conduct inter-disciplinary translational research with clinical partners in Oxford and elsewhere in the UK and overseas in clinical domains of application ranging from fetal development, to oncology, respiratory medicine, gastroenterology, neurology and cardiovascular medicine.

_labs/CpG_mim.md

@@ -0,0 +1,10 @@
+---
+short_name: CpG@MIM
+title: Computational proteomics and genomics group
+head: Anna Gambin
+contact: a.gambin@uw.edu.pl
+logo: ./lab-logo/CpG_small.jpeg
+location: Faculty of Mathematics, Informatics and Mechanics, University of Warsaw
+---
+
+We specialize in designing efficient computational methods and mathematical models for analyzing data from high-throughput biotechnologies, such as mass spectrometry, NMR, HiC, and NGS. We are particularly interested in applications in molecular medicine and issues related to the evolution and stability of the human genome.

_labs/ideas.md

@@ -0,0 +1,11 @@
+---
+short_name: IDEAS
+title: IDEAS NCBR
+head: Piotr Sankowski, Stefan Dziembowski, Tomasz Trzciński, Przemysław Musialski, Paweł Wawrzyński, Krzysztof Stereńczak, Krzysztof Walas
+contact: phd@ideas-ncbr.pl
+logo: ./lab-logo/ideas.png
+website_url: https://ideas-ncbr.pl
+location: Warsaw, Poland
+---
+
+IDEAS NCBR Sp. z o.o. is a research and development centre operating in the field of artificial intelligence and digital economy, whose mission is to support the development of these technologies in Poland by creating a platform that connects the academic and business environments. IDEAS NCBR Sp. z o.o. is a part of the National Center for Research and Development (NCBR Group). Our goal is to build in Poland the largest, friendly to conduct innovative research platform, to educate a new generation of scientists focused on development of algorithms and their subsequent practical application, commercialization in the industry, finance, medicine and other branches of the economy. At IDEAS NCBR, we are constantly on the lookout for new talent. If you are a student or graduate of Mathematics, Computer Science, Information and Communication Technology or a related discipline and would like to pursue a career in research, then share your plans with us.

_labs/rlg.md

@@ -0,0 +1,9 @@
+---
+short_name: RLG
+title: Robot learning group
+head: Marek Cygan
+contact: cygan@mimuw.edu.pl
+location: MIM UW, Banacha 2, Warsaw
+---
+
+Robot learning is a broad domain, that encompasses various aspects of computer vision, reinforcement learning and robotics. Recently the field has become even broader as more and more high level planning algorithms in robotics involve LLMs.

_projects/mlinpl/biomedia_multimodal_learning.md

@@ -0,0 +1,27 @@
+---
+title: Multimodal learning for population health studies
+leader: Bartek Papiez
+contact: bartlomiej.papiez@bdi.ox.ac.uk
+positions:
+    - name: Student researcher
+lab_name: BioMedIA
+deadline: 2024-03-31
+created: 2023-12-31
+location: Oxford, England
+---
+
+Most machine learning methodologies require large datasets with high-quality labelling to effectively train and validate the developed models. However, as medical imaging repositories used for population health studies, such as the UK Biobank, continue to grow, the conventional manual annotation approaches by experts become impractical. On the other hand, the labelling process can be automated by extracting annotations from associated metadata or reports. In such scenarios, automated labelling can introduce errors due to ambiguities in the reports, resulting in large but noisy-labelled (or even mislabelled) datasets. Consequently, this can lead to poorer generalization or replicate human biases present in the data. The primary objective of this project is to investigate machine learning strategies that can guide optimal annotation techniques to achieve high accuracy while mitigating biases in the developed model.
+
+## Student Researcher
+
+### Must-have requiremets
+
+The student will be expected to attend relevant seminars within the department and those relevant in the wider University. Subject-specific training will be received through our group's weekly supervision meetings. Students will also attend external scientific conferences where they will be expected to present the research findings.
+
+### Nice-to-have requiremets 
+
+We would be pleased to see in your application: experience in implementing robotic solutions experience in efficient methods of machine learning, senor data processing, robot control references with min. 1 contact to person, who can recommend you.
+
+## PostDoc
+
+The ideal student would have: a degree in computer science, statistics, engineering or a related discipline strong programming skills (preferable Python, or Matlab/C++ and willing to learn Python) experience or interest in machine learning (Deep Learning) and medical image analysis experience or enthusiasm to work on clinically relevant problems.

_projects/mlinpl/ideas_intelligent_algorithms.md

@@ -0,0 +1,43 @@
+---
+title: Intelligent Algorithms and Learned Data Structures
+leader: Piotr Sankowski, PhD, ScD
+contact: phd@ideas-ncbr.pl
+positions:
+    - name: PhD Candidate
+    - name: PostDoc
+lab_name: IDEAS
+location: Poland
+deadline: 2024-03-31
+created: 2023-10-19
+---
+
+The research group focuses on problems of practical use of algorithms, ranging from economic applications, through learning data structures, to parallel algorithms for data science. Our teams focus not only on scientific development but also on the possibility of the practical application of the created solutions in business and the economy. We create innovations that will soon be implemented, allowing you to see the real effects of your work. If you have similar ambitions, are looking for scientific challenges and want to prove yourself in actual market conditions, we invite you to apply.
+
+### General must-have requirements
+
+If you are a student or graduate of Mathematics, Computer Science, Information Technology or a related discipline and would like to pursue a career in research, then share your plans with us by applying for this position.
+
+## PhD Candidate
+
+You will carry out research and development work related to issues such as: the use of IT tools in the digital economy, learning data structures, algorithms for data science, other related scientific issues. Your work will be research-focused with minimal teaching responsibilities, teaching a minimum of 60 hours per year.
+
+### Must-have requiremets
+
+A degree (Master's or equivalent) in computer science, information technology or a related discipline from a leading university, excellent programming skills, curiosity and great interest in machine learning, artificial intelligence or IT tools for the digital economy, fluency in English.
+
+### Nice-to-have requiremets 
+
+We would be pleased to see in your application: references with min. 1 contact to person, who can recommend you.
+
+## PostDoc
+
+You will carry out research and development work related to issues such as: the use of IT tools in the digital economy, learning data structures, algorithms for data science, other related scientific issues. Your work will be research-focused with minimal teaching responsibilities: teaching a minimum of 60 hours per year.
+
+### Must-have requiremets
+
+Educational background: PhD in Science, preferred majors: Computer Science, or Mathematics or other science majors with experience in working with AI, experience in machine learning, English language skills at an advanced level, very good programming skills, a proactive approach to solving scientific problems and issues, strong analytical and critical thinking skills, ability to work in a team.
+
+### Nice-to-have requiremets 
+
+We would be pleased to see in your application: references with min. 1 contact to person, who can recommend you.
+

_projects/mlinpl/ideas_learing_in_control.md

@@ -0,0 +1,37 @@
+---
+title: Learning in control, graphs and networks
+leader: Paweł Wawrzyński, PhD, DSc
+contact: phd@ideas-ncbr.pl
+positions:
+  - name: PhD Candidate
+lab_name: IDEAS
+location: Poland
+deadline: 2024-03-31
+created: 2023-10-23
+---
+
+The team develops neural networks that generate graphs. These solutions are oriented towards the automatic design of structures naturally represented by graphs, such as molecules or energy networks. Known methods for generating graphs are based on an assumed limitation on the size of the graph and are thus not scalable. How to generate arbitrarily large graphs that meet set functional requirements? We are developing methods that address this challenge. https://ideas-ncbr.pl/en/badania/learning-in-control-graphs-and-networks/
+
+## PhD Candidate
+
+You will carry out research and development work related to issues such as: deep reinforcement learning; automated trading; graph neural networks; energy grid control; continual learning; other related scientific issues. Your work will be research-focused with minimal teaching responsibilities, teaching a minimum of 60 hours per year.
+
+### Must-have requiremets
+
+Programming in Python; knowledge of libraries (at least one): PyTorch, TensorFlow; experience in machine learning; proactive approach to solving scientific problems and issues; strong analytical and critical thinking skills; strong background in mathematics; ability to work in a team; fluency in English.
+
+### Nice-to-have requiremets 
+
+We would be pleased to see in your application: scientific publications, especially at good ML conferences and/or other signs of outstanding academic performance.
+
+## PostDoc
+
+You will carry out research and development work related to issues such as: deep reinforcement learning, automated trading, graph neural networks, energy grid control, continual learning; other related scientific issues. Your work will be research-focused with minimal teaching responsibilities: teaching a minimum of 60 hours per year.
+
+### Must-have requiremets
+
+Programming in Phyton, fluent knowledge of libraries (at least) one: PyTorch, TensorFlow, research experience in machine learning including publications at ML conferences/journals, proactive approach to solving scientific problems and issues, strong analytical and critical thinking skills, strong background in mathematics, ability to work in a team, fluency in English.
+
+### Nice-to-have requiremets 
+
+We would be pleased to see in your application: references with min. 1 contact to person, who can recommend you.

_projects/mlinpl/ideas_neural_rendering.md

@@ -0,0 +1,25 @@
+---
+title: Neural Rendering
+leader: Przemysław Musialski, PhD, Assoc. Prof.
+contact: phd@ideas-ncbr.pl
+positions:
+  - name: PhD Candidate
+lab_name: IDEAS
+location: Poland
+deadline: 2024-03-31
+created: 2023-10-23
+---
+
+With expertise in diverse areas such as geometric modeling, geometry processing, computational fabrication, and machine learning, we strive to create algorithmic solutions for digital content generation. Our research efforts are dedicated to revolutionizing content creation, geometry generation, realistic rendering, and physical simulations in applications ranging from computer games and movie productions to virtual reality and 3D design. As a part of our group, you will have the opportunity to work on cutting-edge research projects, publish in top-tier conferences and journals, and collaborate with a diverse team of experts. This PhD project is an exciting opportunity to delve into the promising and rapidly evolving field of differentiable neural rendering. This is a novel area at the crossroads of machine learning and computer graphics, where traditional rendering techniques meet advanced neural networks. The primary objective of this research is to develop innovative methods for differentiable neural rendering with applications in CGI for visual effects for film, TV, and advertisement productions. The project involves developing a framework where changes in the output image can be traced back to changes in input parameters, such as object shapes, light positions, or material properties. Leveraging this, the project aims to optimize these parameters to improve the quality of the rendered image.
+
+
+# PhD Candidate
+
+### Must-have requiremets
+
+A strong background in computer science, mathematics, or related disciplines; MSc graduate or last year student; experience in machine learning; knowledge of libraries such as TensorFlow or PyTorch; familiarity with differentiable or neural rendering would be an advantage but is not a requirement; proficient programming skills, preferably in Python; proactive approach to solving scientific problems and issues; strong analytical and critical thinking skills; ability to work in a team; fluency in English.
+
+
+### Nice-to-have requiremets 
+
+We would be pleased to see in your application: references with min. 1 contact to people, who can recommend you.

_projects/mlinpl/ideas_robotics.md

@@ -0,0 +1,42 @@
+---
+title: Robotics
+leader: Krzysztof Walas, PhD
+contact: phd@ideas-ncbr.pl
+positions:
+    - name: PhD Candidate
+    - name: PostDoc
+lab_name: IDEAS
+location: Poland
+deadline: 2024-03-31
+created: 2023-10-19
+---
+
+The Independent Research Team aims to challenge the current approach that avoids contacts and intend robots to leverage contacts for perception and action. Focuses on using vision and tactile sensing to provide robots with detailed understanding of the environment's physics. We focus on the scientific development of our employees and the practical application of research results.
+
+### General must-have requirements
+
+If you are a student or graduate of Mathematics, Computer Science, Information and Communication Technology or a related discipline and would like to pursue a career in research, then share your plans with us by applying for this position.
+
+## PhD Candidate
+
+You will carry out research and development work related to issues such as: machine learning methods to enable robots to interact with the environment taking into account physical phenomena of this process, interactive perception, representation learning and reinforcement learning, agile robotic manipulation of deformable objects, other related scientific issues. Your work will be research-focused with minimal teaching responsibilities: teaching a minimum of 60 hours per year.
+
+### Must-have requiremets
+
+Educational background: MSc graduate or last year student, preferred majors: Robotics, Control, Computer Science or other science majors related to robotics and machine learning, experience in robotics and machine learning, practical experience in software development for robotic learning, including programming skills with the use of such libraries as: Robot Operating System 2, Gazebo, MuJoCo,kr PyTorch, TensorFlow, Keras, OpenCV, Open3D, PCL, advanced level of English, very good programming skills, proactive approach to solve problems and scientific issues, excellent analytical and critical thinking skills, ability to work in a team.
+
+### Nice-to-have requiremets 
+
+We would be pleased to see in your application: experience in implementing robotic solutions experience in efficient methods of machine learning, senor data processing, robot control references with min. 1 contact to person, who can recommend you.
+
+## PostDoc
+
+You will carry out research and development work related to issues such as: machine learning methods to enable robots to interact with the environment taking into account physical phenomena of this process, interactive perception, representation learning and reinforcement learning, agile robotic manipulation of deformable objects, other related scientific issues. Your work will be research-focused with minimal teaching responsibilities: teaching a minimum of 60 hours per year.
+
+### Must-have requiremets
+
+Educational background: PhD in Science, preferred majors: Robotics, Control, Computer Science or other science majors related to robotics and machine learning, experience in robotics and machine learning, practical experience in software development for robotic learning, including programming skills with the use of such libraries as: Robot Operating System 2, Gazebo, MuJoCo,kr PyTorch, TensorFlow, Keras, OpenCV, Open3D, PCL scientific publications presented during the most important thematic conferences such as: ICRA, IROS, RSS, CORL or top tier robotics journals such as: Science Robotics, Transactions on Robotics, Robotics and Automation Letters, The International Journal of Robotic Research, Robotics and Autonomous Systems advanced level of English, very good programming skills, proactive approach to solve problems and scientific issues, excellent analytical and critical thinking skills, ability to work in a team.
+
+### Nice-to-have requiremets 
+
+We would be pleased to see in your application: experience in implementing robotic solutions experience in efficient methods of machine learning, senor data processing, robot control references with min. 1 contact to person, who can recommend you.