#avsec

[orlandovasconcelos-blog]

Aviation Security.

[yenipenerbangan]

Berikut adalah jenis-jenis Pekerjaan yang ada di Bandara. =================== Website Pendaftaran www.sekolahpenerbangan.com ===================

[kazifatagar]

New: Surprise Arrival as Passenger Gives Birth to Baby in KLIA Terminal 1 Waiting Area

A surprise birth occurred at Kuala Lumpur International Airport (KLIA), where a passenger delivered her baby in the waiting area of KLIA Terminal 1. The Aviation Security (AVSEC) team promptly sought assistance from the Ministry of Health Malaysia (KKM) and Medilife Paramedic to aid the woman. Social Media Links Follow us on: Instagram Threads Facebook Twitter YouTube DailyMotion Read More…

[rolandrockover]

Some Trains Don't Turn Me On

Bon Jovi are back, and they're not alone, because this time they've brought Ozzy Osbourne along as reinforcement!!!

[note: This would have been my originally intended introduction for today, dear people, but in the end I opted for the following, somewhat less flashy version.]

Tinkering hour with Turn on the Night (1987), and how to put together a hit that didn't want to become one, but preferred to eke out its modest existence as an eternal insider tip in gradually enlightened hardcore fan circles.

There are those who claim that Turn on the Night is a rip-off of Bon Jovi's She Don't Know Me (1984) (1), others, on the other hand, swear their first-born child that they clearly recognize Ozzy's Crazy Train (1980) in it. Even if I personally think that neither party is wrong with their respective assumptions, I belong to the faction that unmistakably recognized the intro of a popular German pop talk show called Na, sowas! from the Saturday evening prime time TV program of the mid-80s in Turn on the Night's anthemic keyboard intro and chorus.

The Bon Jovi comparison certainly applies with his intro and the chorus melody, and Ozzy's verses rather reinforce the impression that Bongiovi and Co. might have already had their way with them before. But if we now add the first few verse lines and Spencer Davis Groups' Gimme Some Lovin' (1966) and above all its flow and feel, this wild affair could slowly become a well-rounded one.

It's written somewhere on the holy internet how Paul spoke out about Diane Warren being the main contributor to Turn on the Night, and Diane Warren herself expressed her surprise that the song didn't become a hit.

My idea to this subject is, it's a bit as if a food designer had designed and developed an attractive and appetizing fast food product inspired from the most popular offerings of the three best-known providers in Western culture in this field, only to be completely ignored by the entire analyzed and potential customer base. Which makes me think once again that sometimes it's not the product itself that counts, but the brand, or at least its promotion (2). I don't know what kind of crazy world we live in that Turn on the Night shouldn't be a hit.

I guess Unmasked's (1980) Tomorrow must have felt something like that.

Side Notes:

(1) You could just as easily accuse Holly Knight of using Bon Jovi's She Don't Know Me for The Best (1988/89), which would of course be complete nonsense, because these kinds of melodies were something of a junction for pop and rock music in the 80s, just as the riff from Smoke on the Water (1972) was more or less a blueprint for rock riffs from the 70s onwards. But it was all up in the air at the time an all you had to do was reach for it and pick it like a ripe fruit.

(2) As I'm writing this, I'm feeling a deja vu to one of my previous entries, namely Nothing Can Keep Me From You (1999), also written by Diane Warren.

The links are all highlighted somewhere, but don't ask me where exactly, because I wrote the above lines more than half a year ago. Let's just trust that everything will be all right:

Turn on the Night (1987)

She Don't Know Me (1984)

Crazy Train (1980)

Gimme Some Lovin' (1966)

1980-F (1980)

[naija247new]

MMA2 Operator Declares Zero Tolerance for Violence as Passenger Assaults Security Officer Over Check-In Glitch

…Bi-Courtney hands over culprit to police for prosecution …Reiterates staff dignity and aviation terminal safety …Incident sparks industry-wide concern over rising airport aggression By Naija247news Aviation Desk | Lagos | April 24, 2025 The management of Bi-Courtney Aviation Services Limited (BASL), operator of Murtala Muhammed Airport Terminal Two (MMA2) in Lagos, has issued a stern warning…

[pendidikanpramugari]

Sekolah AVSEC PSPP Jogja

Sekolah AVSEC PSPP Jogja salah satu tempat diklat AVSEC resmi yang memilki ijin dari Dirjen Perhubungan. PSPP Penerbangan menyelenggarakan diklat AVSEC angkatan Juni 2023. Sekolah AVSEC PSPP Penerbangan adalah salah satu sekolah penerbangan yang berdiri di Yogyakarta. Sekolah ini didirikan pada tahun 2010 oleh PT. Triando Mandiri Investama. Sekolah AVSEC PSPP Penerbangan memiliki tujuan untuk…

[cleverhottubmiracle]

[ad_1] Science Published 25 June 2025 Authors Ziga Avsec and Natasha Latysheva Introducing a new, unifying DNA sequence model that advances regulatory variant-effect prediction and promises to shed new light on genome function — now available via API.The genome is our cellular instruction manual. It’s the complete set of DNA which guides nearly every part of a living organism, from appearance and function to growth and reproduction. Small variations in a genome’s DNA sequence can alter an organism’s response to its environment or its susceptibility to disease. But deciphering how the genome’s instructions are read at the molecular level — and what happens when a small DNA variation occurs — is still one of biology’s greatest mysteries.Today, we introduce AlphaGenome, a new artificial intelligence (AI) tool that more comprehensively and accurately predicts how single variants or mutations in human DNA sequences impact a wide range of biological processes regulating genes. This was enabled, among other factors, by technical advances allowing the model to process long DNA sequences and output high-resolution predictions.To advance scientific research, we’re making AlphaGenome available in preview via our AlphaGenome API for non-commercial research, and planning to release the model in the future.We believe AlphaGenome can be a valuable resource for the scientific community, helping scientists better understand genome function, disease biology, and ultimately, drive new biological discoveries and the development of new treatments.How AlphaGenome worksOur AlphaGenome model takes a long DNA sequence as input — up to 1 million letters, also known as base-pairs — and predicts thousands of molecular properties characterising its regulatory activity. It can also score the effects of genetic variants or mutations by comparing predictions of mutated sequences with unmutated ones.Predicted properties include where genes start and where they end in different cell types and tissues, where they get spliced, the amount of RNA being produced, and also which DNA bases are accessible, close to one another, or bound by certain proteins. Training data was sourced from large public consortia including ENCODE, GTEx, 4D Nucleome and FANTOM5, which experimentally measured these properties covering important modalities of gene regulation across hundreds of human and mouse cell types and tissues. Animation showing AlphaGenome taking one million DNA letters as input and predicting diverse molecular properties across different tissues and cell types. The AlphaGenome architecture uses convolutional layers to initially detect short patterns in the genome sequence, transformers to communicate information across all positions in the sequence, and a final series of layers to turn the detected patterns into predictions for different modalities. During training, this computation is distributed across multiple interconnected Tensor Processing Units (TPUs) for a single sequence.This model builds on our previous genomics model, Enformer and is complementary to AlphaMissense, which specializes in categorizing the effects of variants within protein-coding regions. These regions cover 2% of the genome. The remaining 98%, called non-coding regions, are crucial for orchestrating gene activity and contain many variants linked to diseases. AlphaGenome offers a new perspective for interpreting these expansive sequences and the variants within them. AlphaGenome’s distinctive featuresAlphaGenome offers several distinctive features compared to existing DNA sequence models:Long sequence-context at high resolutionOur model analyzes up to 1 million DNA letters and makes predictions at the resolution of individual letters. Long sequence context is important for covering regions regulating genes from far away and base-resolution is important for capturing fine-grained biological details.Previous models had to trade off sequence length and resolution, which limited the range of modalities they could jointly model and accurately predict. Our technical advances address this limitation without significantly increasing the training resources — training a single AlphaGenome model (without distillation) took four hours and required half of the compute budget used to train our original Enformer model.Comprehensive multimodal predictionBy unlocking high resolution prediction for long input sequences, AlphaGenome can predict the most diverse range of modalities. In doing so, AlphaGenome provides scientists with more comprehensive information about the complex steps of gene regulation.Efficient variant scoringIn addition to predicting a diverse range of molecular properties, AlphaGenome can efficiently score the impact of a genetic variant on all of these properties in a second. It does this by contrasting predictions of mutated sequences with unmutated ones, and efficiently summarising that contrast using different approaches for different modalities.Novel splice-junction modelingMany rare genetic diseases, such as spinal muscular atrophy and some forms of cystic fibrosis, can be caused by errors in RNA splicing — a process where parts of the RNA molecule are removed, or “spliced out”, and the remaining ends rejoined. For the first time, AlphaGenome can explicitly model the location and expression level of these junctions directly from sequence, offering deeper insights about the consequences of genetic variants on RNA splicing.State-of-the-art performance across benchmarksAlphaGenome achieves state-of-the-art performance across a wide range of genomic prediction benchmarks, such as predicting which parts of the DNA molecule will be in close proximity, whether a genetic variant will increase or decrease expression of a gene, or whether it will change the gene’s splicing pattern. Bar graph showing AlphaGenome’s relative improvements on selected DNA sequence and variant effect tasks, compared against results for the current best methods in each category. When producing predictions for single DNA sequences, AlphaGenome outperformed the best external models on 22 out of 24 evaluations. And when predicting the regulatory effect of a variant, it matched or exceeded the top-performing external models on 24 out of 26 evaluations.This comparison included models specialized for individual tasks. AlphaGenome was the only model that could jointly predict all of the assessed modalities, highlighting its generality. Read more in our preprint.The benefits of a unifying modelAlphaGenome’s generality allows scientists to simultaneously explore a variant's impact on a number of modalities with a single API call. This means that scientists can generate and test hypotheses more rapidly, without having to use multiple models to investigate different modalities.Moreover AlphaGenome’s strong performance indicates it has learned a relatively general representation of DNA sequence in the context of gene regulation. This makes it a strong foundation for the wider community to build upon. Once the model is fully released, scientists will be able to adapt and fine-tune it on their own datasets to better tackle their unique research questions.Finally, this approach provides a flexible and scalable architecture for the future. By extending the training data, AlphaGenome’s capabilities could be extended to yield better performance, cover more species, or include additional modalities to make the model even more comprehensive. “ It’s a milestone for the field. For the first time, we have a single model that unifies long-range context, base-level precision and state-of-the-art performance across a whole spectrum of genomic tasks. Dr. Caleb Lareau, Memorial Sloan Kettering Cancer Center A powerful research toolAlphaGenome's predictive capabilities could help several research avenues:Disease understanding: By more accurately predicting genetic disruptions, AlphaGenome could help researchers pinpoint the potential causes of disease more precisely, and better interpret the functional impact of variants linked to certain traits, potentially uncovering new therapeutic targets. We think the model is especially suitable for studying rare variants with potentially large effects, such as those causing rare Mendelian disorders.Synthetic biology: Its predictions could be used to guide the design of synthetic DNA with specific regulatory function — for example, only activating a gene in nerve cells but not muscle cells.Fundamental research: It could accelerate our understanding of the genome by assisting in mapping its crucial functional elements and defining their roles, identifying the most essential DNA instructions for regulating a specific cell type's function.For example, we used AlphaGenome to investigate the potential mechanism of a cancer-associated mutation. In an existing study of patients with T-cell acute lymphoblastic leukemia (T-ALL), researchers observed mutations at particular locations in the genome. Using AlphaGenome, we predicted that the mutations would activate a nearby gene called TAL1 by introducing a MYB DNA binding motif, which replicated the known disease mechanism and highlighted AlphaGenome’s ability to link specific non-coding variants to disease genes. “ AlphaGenome will be a powerful tool for the field. Determining the relevance of different non-coding variants can be extremely challenging, particularly to do at scale. This tool will provide a crucial piece of the puzzle, allowing us to make better connections to understand diseases like cancer. Professor Marc Mansour, University College London Current limitationsAlphaGenome marks a significant step forward, but it's important to acknowledge its current limitations.Like other sequence-based models, accurately capturing the influence of very distant regulatory elements, like those over 100,000 DNA letters away, is still an ongoing challenge. Another priority for future work is further increasing the model’s ability to capture cell- and tissue-specific patterns.We haven't designed or validated AlphaGenome for personal genome prediction, a known challenge for AI models. Instead, we focused more on characterising the performance on individual genetic variants. And while AlphaGenome can predict molecular outcomes, it doesn't give the full picture of how genetic variations lead to complex traits or diseases. These often involve broader biological processes, like developmental and environmental factors, that are beyond the direct scope of our model.We’re continuing to improve our models and gathering feedback to help us address these gaps.Enabling the community to unlock AlphaGenome's potentialAlphaGenome is now available for non-commercial use via our AlphaGenome API. Please note that our model’s predictions are intended only for research use and haven’t been designed or validated for direct clinical purposes.Researchers worldwide are invited to get in touch with potential use-cases for AlphaGenome and to ask questions or share feedback through the community forum.We hope AlphaGenome will be an important tool for better understanding the genome and we’re committed to working alongside external experts across academia, industry, and government organizations to ensure AlphaGenome benefits as many people as possible.Together with the collective efforts of the wider scientific community, we hope it will deepen our understanding of the complex cellular processes encoded in the DNA sequence and the effects of variants, and drive exciting new discoveries in genomics and healthcare. Learn more about AlphaGenome AcknowledgementsWe would like to thank Juanita Bawagan, Arielle Bier, Stephanie Booth, Irina Andronic, Armin Senoner, Dhavanthi Hariharan, Rob Ashley, Agata Laydon and Kathryn Tunyasuvunakool for their help with the text and figures.This work was done thanks to the contributions of the AlphaGenome co-authors: Žiga Avsec, Natasha Latysheva, Jun Cheng, Guido Novati, Kyle R. Taylor, Tom Ward, Clare Bycroft, Lauren Nicolaisen, Eirini Arvaniti, Joshua Pan, Raina Thomas, Vincent Dutordoir, Matteo Perino, Soham De, Alexander Karollus, Adam Gayoso, Toby Sargeant, Anne Mottram, Lai Hong Wong, Pavol Drotár, Adam Kosiorek, Andrew Senior, Richard Tanburn, Taylor Applebaum, Souradeep Basu, Demis Hassabis and Pushmeet Kohli.We would also like to thank Dhavanthi Hariharan, Charlie Taylor, Ottavia Bertolli, Yannis Assael, Alex Botev, Anna Trostanetski, Lucas Tenório, Victoria Johnston, Richard Green, Kathryn Tunyasuvunakool, Molly Beck, Uchechi Okereke, Rachael Tremlett, Sarah Chakera, Ibrahim I. Taskiran, Andreea-Alexandra Muşat, Raiyan Khan, Ren Yi and the greater Google DeepMind team for their support, help and feedback. [ad_2] Source link

[orlandovasconcelos-blog]

Great Example of Life transformation.

My answer to What are examples of successful life transformations you've witnessed or experienced? https://www.quora.com/What-are-examples-of-successful-life-transformations-youve-witnessed-or-experienced/answer/Orlando-Vasconcelos?ch=15&oid=1477743846954295&share=660d761c&srid=peZL&target_type=answer

[kiddoschools]

Airport Job Vacancies 2025 - AVSEC Trainee #jobvacancies #srilanka #jobvacancy #career #opportunities

[criativaonline]

Brasil atualiza normas da aviação civil para mais segurança

A Força Aérea Brasileira (FAB) divulgou que, em março de 2025, deu início às inspeções de Segurança Operacional e de Segurança da Aviação Civil contra Atos de Interferência Ilícita (AVSEC). Essas inspeções analisam se as normas do Departamento de Controle do Espaço Aéreo (DECEA) estão sendo seguidas e objetivam garantir a conformidade e eficiência dos Provedores de Serviços de Navegação Aérea…

[ljlcorp]

Lowongan Kerja dari PT. Garuda Daya Pratama Sejahtera (GDPS) Maret 2025

Berikut kami sampaikan informasi Lowongan Kerja dari PT. Garuda Daya Pratama Sejahtera (GDPS).

PT. Garuda Daya Pratama Sejahtera (GDPS) berdiri sebagai perusahaan jasa penyedia dan pengelola tenaga kerja untuk memenuhi kebutuhan tenaga kerja dengan spesialisasi di bidang Aviasi. Saat ini GDPS bertansformasi menjadi perusahaan Business Processing Outsourcing berbasis teknologi 4.0 yang tidak hanya melayani kebutuhan aviasi namun juga merambah ke bisnis lain. Karena GDPS lahir dan merupakan bagian dari Industri Aviasi, sehingga produk dan jasa inovatif yang kami tawarkan berbasis 3 aspek utama yaitu Kompetensi dan Teknologi serta memperhatikan aspek HSSE

PT. GDPS berdiri dengan kepemilikan saham mayoritas dari PT. Garuda Maintenance Facility Aero Asia Tbk (Anak Perusahaan PT. Garuda Indonesia Tbk) dan kepemilikan saham minoritas dari koperasi Karyawan GMF.

PT. GDPS didukung oleh tenaga-tenaga kerja yang berintegritas dan profesional. Pelatihan dan penanaman nilai-nilai perusahaan juga terus dilakukan secara berkala dalam rangka peningkatan kemampuan softskill dan hardskill karyawan.

Sampai saat ini GDPS telah mengelola tenaga kerja yang berjumlah puluhuan ribu dengan lokasi penempatan yang tersebar di lebih dari 55 kota di wilayah Indonesia dengan berbagai area kerja mulai dari teknisi pesawat, data entry, IT support, Building management, security, passanger assistant, SPG, SPB sampai dengan tenaga kerja di industri manufaktur.

Saat ini, PT. Garuda Daya Pratama Sejahtera (GDPS) membuka lowongan kerja di kota Medan, Sumatera Utara untuk posisi berikut ini:

Human Capital Officer

Business Analyst

Aviation Security (Avsec)

Field Operation Staff

Pendukung Operasional Cargo

Security

Driver B1

Selengkapnya baca di 👇👇👇 https://www.lokerinone.com/2023/11/pt-garuda-daya-pratama-sejahtera-gdps.html

[readbossy]

Airport Job Vacancies 2025 - Aviation Security Professional (AVSEC) Trainee

[cleverhottubmiracle]

[ad_1] Research Published 19 September 2023 Authors Žiga Avsec and Jun Cheng New AI tool classifies the effects of 71 million ‘missense’ mutations Uncovering the root causes of disease is one of the greatest challenges in human genetics. With millions of possible mutations and limited experimental data, it’s largely still a mystery which ones could give rise to disease. This knowledge is crucial to faster diagnosis and developing life-saving treatments. Today, we’re releasing a catalogue of ‘missense’ mutations where researchers can learn more about what effect they may have. Missense variants are genetic mutations that can affect the function of human proteins. In some cases, they can lead to diseases such as cystic fibrosis, sickle-cell anaemia, or cancer. The AlphaMissense catalogue was developed using AlphaMissense, our new AI model which classifies missense variants. In a paper published in Science, we show it categorised 89% of all 71 million possible missense variants as either likely pathogenic or likely benign. By contrast, only 0.1% have been confirmed by human experts.AI tools that can accurately predict the effect of variants have the power to accelerate research across fields from molecular biology to clinical and statistical genetics. Experiments to uncover disease-causing mutations are expensive and laborious – every protein is unique and each experiment has to be designed separately which can take months. By using AI predictions, researchers can get a preview of results for thousands of proteins at a time, which can help to prioritise resources and accelerate more complex studies. We’ve made all of our predictions freely available for commercial and researcher use, and open sourced the model code for AlphaMissense. AlphaMissense predicted the pathogenicity of all possible 71 million missense variants. It classified 89% – predicting 57% were likely benign and 32% were likely pathogenic. What is a missense variant?A missense variant is a single letter substitution in DNA that results in a different amino acid within a protein. If you think of DNA as a language, switching one letter can change a word and alter the meaning of a sentence altogether. In this case, a substitution changes which amino acid is translated, which can affect the function of a protein. The average person is carrying more than 9,000 missense variants. Most are benign and have little to no effect, but others are pathogenic and can severely disrupt protein function. Missense variants can be used in the diagnosis of rare genetic diseases, where a few or even a single missense variant may directly cause disease. They are also important for studying complex diseases, like type 2 diabetes, which can be caused by a combination of many different types of genetic changes.Classifying missense variants is an important step in understanding which of these protein changes could give rise to disease. Of more than 4 million missense variants that have been seen already in humans, only 2% have been annotated as pathogenic or benign by experts, roughly 0.1% of all 71 million possible missense variants. The rest are considered ‘variants of unknown significance’ due to a lack of experimental or clinical data on their impact. With AlphaMissense we now have the clearest picture to date by classifying 89% of variants using a threshold that yielded 90% precision on a database of known disease variants.Pathogenic or benign: How AlphaMissense classifies variantsAlphaMissense is based on our breakthrough model AlphaFold, which predicted structures for nearly all proteins known to science from their amino acid sequences. Our adapted model can predict the pathogenicity of missense variants altering individual amino acids of proteins.To train AlphaMissense, we fine-tuned AlphaFold on labels distinguishing variants seen in human and closely related primate populations. Variants commonly seen are treated as benign, and variants never seen are treated as pathogenic. AlphaMissense does not predict the change in protein structure upon mutation or other effects on protein stability. Instead, it leverages databases of related protein sequences and structural context of variants to produce a score between 0 and 1 approximately rating the likelihood of a variant being pathogenic. The continuous score allows users to choose a threshold for classifying variants as pathogenic or benign that matches their accuracy requirements. An illustration of how AlphaMissense classifies human missense variants. A missense variant is input, and the AI system scores it as pathogenic or likely benign. AlphaMissense combines structural context and protein language modelling, and is fine-tuned on human and primate variant population frequency databases. AlphaMissense achieves state-of-the-art predictions across a wide range of genetic and experimental benchmarks, all without explicitly training on such data. Our tool outperformed other computational methods when used to classify variants from ClinVar, a public archive of data on the relationship between human variants and disease. Our model was also the most accurate method for predicting results from the lab, which shows it is consistent with different ways of measuring pathogenicity. AlphaMissense outperforms other computational methods on predicting missense variant effects.Left: Comparing AlphaMissense and other methods’ performance on classifying variants from the Clinvar public archive. Methods shown in grey were trained directly on ClinVar and their performance on this benchmark are likely overestimated since some of their training variants are contained in this test set.Right: Graph comparing AlphaMissense and other methods’ performance on predicting measurements from biological experiments. Building a community resource AlphaMissense builds on AlphaFold to further the world’s understanding of proteins. One year ago, we released 200 million protein structures predicted using AlphaFold – which is helping millions of scientists around the world to accelerate research and pave the way toward new discoveries. We look forward to seeing how AlphaMissense can help solve open questions at the heart of genomics and across biological science.We’ve made AlphaMissense’s predictions freely available to both commercial and scientific communities. Together with EMBL-EBI, we are also making them more usable through the Ensembl Variant Effect Predictor.In addition to our look-up table of missense mutations, we’ve shared the expanded predictions of all possible 216 million single amino acid sequence substitutions across more than 19,000 human proteins. We’ve also included the average prediction for each gene, which is similar to measuring a gene's evolutionary constraint – this indicates how essential the gene is for the organism’s survival. Examples of AlphaMissense predictions overlaid on AlphaFold predicted structures (red=predicted as pathogenic, blue=predicted as benign, grey=uncertain). Red dots represent known pathogenic missense variants, blue dots represent known benign variants from the ClinVar database.Left: HBB protein. Variants in this protein can cause sickle cell anaemia.Right: CFTR protein. Variants in this protein can cause cystic fibrosis.  Accelerating research into genetic diseasesA key step in translating this research is collaborating with the scientific community. We have been working in partnership with Genomics England, to explore how these predictions could help study the genetics of rare diseases. Genomics England cross-referenced AlphaMissense’s findings with variant pathogenicity data previously aggregated with human participants. Their evaluation confirmed our predictions are accurate and consistent, providing another real-world benchmark for AlphaMissense.While our predictions are not designed to be used in the clinic directly – and should be interpreted with other sources of evidence – this work has the potential to improve the diagnosis of rare genetic disorders, and help discover new disease-causing genes.Ultimately, we hope that AlphaMissense, together with other tools, will allow researchers to better understand diseases and develop new life-saving treatments.  Learn more about AlphaMissense: Notes*As of 13 March 2024 the AlphaMissense predictions are available under a CC BY v.4 license, thereby lifting the previous non-commercial use restriction.  Please see published database and Zenodo for further access information. We would like to thank Juanita Bawagan, Jess Valdez, Katie McAtackney, Kathryn Seager, Hollie Dobson, for their help with text and figures. We are also grateful to our external partners, Genomics England and EMBL-EBI, for their continuous support. This work was done thanks to the contributions of the co-authors: Guido Novati, Joshua Pan, Clare Bycroft, Akvilė Žemgulytė, Taylor Applebaum, Alexander Pritzel, Lai Hong Wong, Michal Zielinski, Tobias Sargeant, Rosalia G. Schneider, Andrew W. Senior, John Jumper, Demis Hassabis, Pushmeet Kohli. We would also like to thank Kathryn Tunyasuvunakool, Rob Fergus, Eliseo Papa, David La, Zachary Wu, Sara-Jane Dunn, Kyle R. Taylor, Natasha Latysheva, Hamish Tomlinson, Augustin Žídek, Roz Onions, Mira Lutfi, Jon Small, Molly Beck, Annette Obika, Hannah Gladman, Folake Abu, Alyssa Pierce, James Tam, Q Green, Meera Last, Tharindi Hapuarachchi and the greater Google DeepMind team for their support, help and feedback. [ad_2] Source link

[orlandovasconcelos-blog]

My answer to When you're a mentor, what things do you learn that you never expected? https://www.quora.com/When-youre-a-mentor-what-things-do-you-learn-that-you-never-expected/answer/Orlando-Vasconcelos?ch=15&oid=1477743832833469&share=ee26ae09&srid=peZL&target_type=answer

[3dassurance]

‘Security is a corporate asset’ asserted Andy Blackwell and John Wood while discussing the management of this asset through the concept of Security Management Systems (SeMS).

https://www.linkedin.com/posts/rania-khbais-msc-afhea-araes-992b0427_bnu-aviationsecurity-avsec-activity-7298633538701045760-bh_m?utm_source=share&utm_medium=member_ios&rcm=ACoAAAAxffoB5WldBFqifXCv7rcodML21Zq2Ons

[shoshanews]

Listing Reference: Fidelity Security Officer - Grade C | Kempton Park - ACSA Permit NeededListing Status: Open Position Summary Company: Fidelity Services GroupIndustry: Security and InvestigationsJob Category: OperationsLocation: Benoni, GautengContract Type: PermanentRemuneration: Market RelatedEE Position: YesClosing Date: 07 March 2025 Introduction Fidelity Security Officers - Grade C Fidelity Services Group, a leader in the security and investigations industry, is hiring a Grade C Security Officer for Kempton Park. This position requires an ACSA Permit and AVSEC training, making it an excellent opportunity for experienced security personnel seeking stable employment in the East Rand region. Candidates must have a minimum of two years in the security industry, be physically fit, and have no criminal record. This role involves safeguarding, patrolling, and entrance/exit control. Job Description The successful candidate will play a critical role in maintaining security at an ACSA-permitted location. Responsibilities include patrolling, safeguarding assets, enforcing security regulations, and reporting incidents in compliance with Fidelity Services Group standards. A detail-oriented and vigilant approach is necessary to ensure the safety of people and property. Ideal Candidate The ideal candidate for this role should meet the following criteria: - Minimum Grade 10 qualification - Grade C accredited and registered security certification - At least two years of experience in the security industry - No criminal record (regular criminal checks required) - Physically fit to perform patrolling and security duties - Must reside in Kempton Park or nearby areas - AVSEC trained (compulsory) - Possession of an ACSA Permit Role Responsibilities - Conduct security patrols to monitor premises and report any unusual activity - Safeguard premises and assets against security threats - Control entrances and exits to prevent unauthorized access - Complete relevant security registers as per company guidelines - Maintain high visibility to deter unlawful activities - Prepare incident and observation reports - Ensure compliance with security regulations and protocols - Act swiftly in emergency situations to mitigate risks - Follow standard operating procedures as per training guidelines Skills & Attributes - Strong communication skills to interact with personnel and visitors - Ability to work effectively under pressure in high-security environments - Excellent attention to detail when monitoring surroundings - Ability to follow instructions accurately and maintain protocol compliance - Strong problem-solving skills to handle security challenges - Ability to work independently and as part of a team - High level of integrity and professionalism Why Join Fidelity Services Group? Fidelity Services Group is committed to fair employment practices and career development. By joining the team, security professionals gain access to: - Career growth within a reputable security company - Training and skill development opportunities - A supportive and diverse work environment - Competitive remuneration packages - Stable employment in a trusted security firm Application Process Interested candidates who meet the criteria should submit their applications before the closing date of 07 March 2025. Shortlisted candidates will be contacted within 10 working days after the closing date. If no response is received within this period, consider the application unsuccessful. Fidelity Services Group supports historically disadvantaged candidates and encourages applications from black female candidates. The company upholds ethical recruitment practices and is dedicated to developing its workforce to meet the highest industry standards. This opportunity at Fidelity Services Group is perfect for security professionals with the necessary credentials and experience. As a Grade C Security Officer, you will play a vital role in safeguarding premises while adhering to high-security protocols. If you meet the qualifications and are passionate about security, apply today to take the next step in your career. Click here to apply Read the full article